A Convenient Vision-based System for Automatic Detection of Parking Spaces in Indoor Parking Lots Using Wide-Angle Cameras

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1 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 A Connint Vision-basd Systm for Automatic Dtction of Parking Spacs in Indoor Parking Lots Using Wid-Angl Camras Shn-En Shih and Wn-Hsiang Tsai, Snior Mmbr, IEEE Abstract A connint indoor ision-basd parking lot systm using wid-angl fishy-lns or catadioptric camras is proposd, which is asy to st up by a usr with no tchnical background. Easinss in th systm stup coms mainly from th us of a nw camra modl which can b calibratd using only on spac lin without knowing its position and dirction, as wll as from th allowanc of connint changs of th dtctd parking spac boundaris. Aftr camra calibration basd on th nw camra modl is compltd, parking-spac boundary lins ar xtractd automatically from input wid-angl imags by a modifid Hough transform with a nw cll accumulation schm, which can gnrats mor accurat qual-width curs using th gomtric rlations of lin positions and dirctions. Also, th usr may asily add or rmo th boundary lins by singl clicks on imags, and parking spacs can b sgmntd out by rgion growing by th us of th boundary lins. Finally, acant parking spacs can b dtctd by a background subtraction schm. A ral ision-basd parking lot has bn stablishd and rlant xprimnts conductd. Good xprimntal rsults show th corrctnss, fasibility, and robustnss of th proposd mthods. Indx Trms wid-angl camras, spac lin analysis, Hough Transform, parking lot analysis, parking lot systm. I. INTRODUCTION owadays, mor and mor camras ar quippd in our Nnironmnt for arious applications lik ido surillanc, nt rcording, idnc collction, tc. In this study, w instigat th us of camras for parking lot managmnt. Most camras usd in parking lot systms ar prspcti ons; wid-angl camras, such as fishy-lns or catadioptric ons, ar not commonly adoptd yt. No mattr what typs of camra systms ar usd, on problm in using thm is th complicatd systm stup procdur, including camra calibration, nironmnt larning, objct modling, tc., whos implmntation usually rquirs th usr to ha a lot of tchnical knowldg. In addition, finding acant parking This work was supportd in part by th NSC, Taiwan undr Grant No E and in part by th Ministry of Education, Taiwan undr th 5-yar Projct of Aiming for th Top Unirsity from 2011 through S. E. Shih is with th Institut of Computr Scinc and Enginring, National Chiao Tung Unirsity, Hsinchu, Taiwan ptr159.cs98g@nctu.du.tw. W. H. Tsai is with th Dpartmnt of Computr Scinc, National Chiao Tung Unirsity, Hsinchu, Taiwan H is also with th Dpartmnt of Information Communication, Asia Unirsity, Taichung, Taiwan whtsai@cis.nctu.du.tw. spacs is oftn a troubl for popl, spcially in larg indoor parking lots on has to spnd much tim with concntration to dri through th ntir parking ara to sarch isually for a acant spac if th parking lot is narly fully occupid. From ths iwpoints, this study aims to dlop an intllignt ision-basd systm using wid-angl camras for parking lot managmnt which has th following two mrits: 1) th camra systm can b st up asily by a common usr with no tchnical background; 2) parking spacs can b dtctd prcisly; and 3) acant parking spacs can b idntifid automatically for connint car parking. About th xisting ision-basd parking lot systms which us only prspcti camras, Blumr t al. [1] dtctd acant parking spacs by a singl prspcti camra using dg and road color information and constructd th rgions of th parking spacs manually. Huang and Wang [2] dtctd acant parking spacs by prspcti camras and usd a thr-layr Baysian hirarchical framwork to tackl th problms of luminanc ariations, shadow ffcts, occlusions among hicls, tc. aftr th 3D modls of th parking spacs wr constructd in adanc. Ichihashi t al. [3] dtctd acant parking spacs using prspcti camras basd on fuzzy c-mans clustring and particl swarm optimization, and markd th rgions of parking spacs manually. Lixia and Dalin [4] dtrmind th acancy of a parking spac basd on imag sgmntation and local binary pattrns, proiding that th pixls of th parking spac ar known in adanc. In ths mthods, th rgions of th parking spacs wr sgmntd out manually. On th contrary, th mthod proposd in this study aims to conduct this major stp automatically in ordr to construct an asy-to-st-up systm. As to camra calibration which also influncs th conninc of th systm usag, th goal of this study is to proid a smart calibration procss for a wid-angl camra, which can b prformd asily by a normal usr with no tchnical knowldg. It is dsird to utiliz only a singl imag of th application nironmnt and common faturs xisting in it without knowing thir dirctions, positions, tc. Many slf-calibration mthods ha bn proposd to mak th calibration procss asy. Dng t al. [5] proposd a mthod to calibrat a cntral (singl-iwpoint) catadioptric camra by th us of a 1D objct with unknown motions by driing th

2 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 2 principal point and th imag cntr first, followd by calculating th focal lngth, skw factor, and mirror paramtrs of th camra. Ramalingam t al. [6] calibratd th projction rays of a cntral camra purly from matchs btwn imags. Gasparini t al. [7] showd that at last thr homographis obtaind from a grid-pattrn board ar rquird to calibrat a gnral cntral camra, and a singl homography is nough to calibrat a parabolic catadioptric camra. Th indoor parking lot systm proposd in this study utilizs multipl wid-angl camras affixd on th ciling and looking downward rtically. Th systm oprations can b diidd into four stags as shown in Fig. 1: camra calibration, spac lin dtction, parking spac sgmntation, and acancy dtction. In th first stag, a nw camra modl is proposd, lading to th uss of fwr paramtrs than conntional modls and a singl spac lin for calibrating th modl. This is why th proposd calibration procss can b don by a usr with no tchnical background. In th scond stag, spac lins apparing in th capturd imag ar dtctd by an dg dtction procss, followd by a Hough transform basd on a nw cll accumulation schm. Equal-width curs ar so gnratd, lading to mor prcis spac lin dtction rsults for us as th boundary lins of th parking spacs. Fig. 1. Th proposd parking lot systm. following mrits: 1) wid-angl camras ar usd so that lss camras ar ndd to cor th ara of a gin parking lot; 2) th camra systm can b calibratd using only on lin in th nironmnt, so that th systm can b st up asily by a usr with no tchnical background; 3) th proposd Hough transform with th nw cll accumulation schm gnrats qual-width curs, so that th proposd systm is capabl of daling dirctly with distortd imags capturd by wid-angl camras and th spac lin dtction rsults ar mor prcis than thos yildd by conntional mthods; 4) unlik many prious studis which spcify parking spacs manually, th proposd mthod dtcts thm automatically for connint systm stup as wll. In th rmaindr of this papr, th dtails of th proposd calibration schm is dscribd in Sc. II, th proposd spac lin dtction mthod is dscribd in Sc. III, and th proposd parking spac sgmntation and acancy dtction tchniqus ar prsntd in Sc. IV. Exprimntal rsults and discussions ar proidd in Sc. V to show th corrctnss, fasibility, and robustnss of th proposd mthod. II. PROPOSED CAMERA MODEL AND CALIBRATION METHOD To dsign an asy-to-stup ision-basd parking lot systm, th camra calibration procss must b asy to carry out by normal usrs with no tchnical knowldg. In this study, a simplifid camra modl is proposd for this aim. A calibration mthod is proposd accordingly which maks us of only on spac lin in th nironmnt without knowing its position and dirction. In th following, an xisting unifying camra modl for wid-angl camras is brifly riwd first in Sc. II.A. Thn, th proposd camra modl is dscribd in Sc. II.B, and th proposd calibration mthod is prsntd in Sc. II.C. A. Riw of a Unifying Modl for Wid-Angl Camras In th unifying modl proposd by Gyr and Daniilidis [8], th rlation btwn a spac point P and its corrsponding pixl p is dscribd by a two-stp mapping ia a unit sphr as illustratd in Fig. 2. Spcifically, point P is firstly projctd onto a point P s on th unit sphr lik bing iwd from th ffcti iwpoint O through th sphr. Thn, P s is projctd prspctily into th pixl p on th imag plan lik bing iwd from th pinhol point O c (usually th lns cntr). Th two inold paramtrs l and f as illustratd in Fig. 2 ar dfind in th sam way as suggstd by Ying and Hu [9]. In th third stag, th dtctd boundary lins ar analyzd and displayd automatically, and th usr can thn simply click on th imag to add or rmo th boundary lins. In addition, by clicking on any position within ach parking spac, th spac rgion is gnratd by a rgion growing procss. Finally, aftr larning th background paramtrs of th acant parking spacs for arious nironmnt conditions, acant spacs can b found by background subtraction for uss in parking managmnt. Th proposd ision-basd parking lot systm has at last th Fig. 2. An illustration of a two-stp sphrical mapping.

3 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 3 Th unifying modl dscribd abo has bn prod quialnt to modls for prspcti, parabolic catadioptric, and hyprbolic catadioptric camras [8]. Additionally, it was shown by Ying and Hu [10] to b suitabl for modling fishy-lns camras as wll. In this study, w simplify it to modl fishy-lns and hyprbolic catadioptric camras, as dscribd nxt. B. Proposd Camra Modl for Wid-Angl Camras Th proposd simplifid unifying camra modl is basd on th us of an optimal approximation alu of th paramtr l which is th distanc from th ffcti iwpoint O to th pinhol point O c as shown in Fig. 2. Th modl has two mrits: 1) it rsrs important charactristics of spac lins as shown in this sction; and 2) it can b calibratd asily by th us of a singl spac lin as dscribd in Sc. II.C. Ths mrits mak th corrsponding systm stup procss asy to conduct. Th rational of finding a fixd optimal alu of paramtr l can b xplaind as follows. In Fig. 3, th imag of a spac lin, calld lin imag hraftr, is markd as a blu cur; and in Fig. 3, this lin imag is shown to b fit wll nough by conic sctions (i.., by Eq. (2) drid latr in this sction) with diffrnt alus of th paramtr l whil th two anishing points ar fixd (markd in yllow in th figur). This phnomnon lads to two conclusions: 1) th paramtr l cannot b wll calibratd from lin imags; and 2) rrsly, th alu of th paramtr l did not affct th spac lin dtction procss. Th first conclusion is consistnt with som prious studis [9][11]. Spcifically, th paramtr l was fixd in th simulation xprimnts dscribd in Gyr and Daniilidis [9], so th paramtr l was not drid in th calibration procss; and as sn in Dng t al. [11], th paramtr l is assumd to b known bfor th calibration. Th scond conclusion maks it possibl to find an optimal alu of th paramtr l to approximat that of any kind of wid-angl camra, without affcting th spac lin dtction procss. intrsting rang of th paramtr l to b 0.5 < l < 2.0, which includs th commonly usd alus of l. For xampl, th alus of l drid in [9][11] ar 0.8, and 1.0, that drid in [12] is , and that drid in [7] is Thn, th optimal alu l of l is found by a simulation procss as dscribd in th following. 1) Gnrat simulatd lin imags I i with siz for a st of sampld alus of l in th intrsting rang 0.5 < l < 2.0 and for a st of sampld positions and dirctions of spac lins; 2) For ach sampl alu l j in th rang 0.5 < l j < 2.0, do th following stps 2.1) through 2.3): 2.1) find th bst-fitting cur I ij to ach lin imag I i, whr I ij is computd by Eq. (2) with l = l j dscribd in Sc. II.C and a Lnbrg Marquardt procss; 2.2) comput th distanc dist ij btwn I i and I ij as 1 n ij k k n k 1 dist p p whr n dnots th numbr of pixls on th lin imag I i, p k a pixl on I i, p k th narst pixl on I ij to p k, and p k p k th distanc btwn p k and p k ; 2.3) calculat th arag distanc dist j of all dist ij of all I i as a masur of optimality of th sampld alu l j, with a smallr dist j maning a bttr fit of l j to all I i. 3) Choos as th dsird optimal alu l th l j with th smallst dist j which is calld also th arag fitting rror and dnotd as dist subsquntly. An xprimntal rsult of th abo procss is shown in Fig. 4, whr Fig. 4 shows a lin imag I i markd in blu and a bst-fitting cur I ij markd in rd; Fig. 4 shows th trnd of th alu of dist j for diffrnt l j alus, from which it can b sn that an optimal alu of l i dos xist and is locatd at 1.24 for choic as l, and that th lin imags can b wll approximatd by Eq. (2) with l = l rsulting in an arag fitting rror dist pixls. Fig. 3. Fitting a spac lin using diffrnt alus of l. Spac lin to b fit (markd as blu). Fitting rsults using l = 2.0, 1.5, 1.0, 0.8, and 0.5 with largr llipss corrsponding to smallr alus of l, and th two yllow crosss indicat th fixd anishing points. To find th optimal alu of l, w dfin first th rang of paramtr l of ach kind of wid-angl camra. For parabolic catadioptric camras, th alu of l is known to b 1.0 [8]; for hyprbolic catadioptric camras, th alu of l is smallr than 1.0 and largr than 0.0 [8]; and for fishy-lns camras, th alu of l is largr than 1.0 [10]. In this study, w dfin th Fig. 4. Finding th optimal alu l. A lin imag I i (markd in blu) and its bst-fitting cur I ij (markd in rd). Th trnd of th arag dist j of th distancs btwn th bst-fitting cur and th lin imags. Th optimal alu of l j is 1.24, with dist j = dist bing about pixls. As a rsult of utilizing th aformntiond scond conclusion, w propos a camra modl which is idntical to th unifying on proposd in [8] but with its paramtr l fixd

4 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 4 to b th optimal alu 1.24 drid priously. On mrit of this modl is that it lads to th possibility of calibrating wid-angl camras using only on lin imag. This proprty is a grat adantag or th conntional modls [8][13], by which th camra cannot b calibratd rliably from lin imags as prod priously in Sc. II.B. It also facilitats a non-tchnical usr to conduct th calibration procss without difficulty as mntiond priously. C. Proposd Calibration Mthod using Only On Spac Lin Basd on th proposd camra modl using th fixd paramtr l = 1.24, th ida of th proposd calibration procss using a singl lin can b diidd into thr stps. First, a spac lin is chosn with its lin imag (in th shap of a conic-sction cur) markd manually. Thn, th bst-fitting llips to this lin imag is computd, from which th unknown camra paramtrs and th spac lin ar stimatd roughly. Finally, a Lnbrg Marquardt algorithm is conductd to find th prcis alus of th camra paramtrs. In mor dtail, lt L b a chosn spac lin, I L its lin imag, and E L th bst-fitting llips to I L. As drid in [9][13], I L can b xprssd as T u l 2 1n 2 2 x l nz l 1nxny fnzn x u 2 Fu, l 1nxny l 1ny l nz fnzn y 0 1 fnn 1 z x fnn z y f n z whr (u, ) ar coordinats of pixls on I L, (n x, n y, n z) is th normal ctor of th plan formd by lin L and th origin of th camra s lns cntr, and (l, f ) ar th paramtrs usd in th unifying camra modl as dscribd in Sc. II.A. Also, lt th llips E L b dscribd by T u a b du b c 0 1 d f 1 Not that whn n z = 0, th lin imag is a straight on going through th imag cntr so that th paramtr f, which is th ffcti focal lngth of th camra, cannot b calibratd [9][14]. Ignoring this, w may rwrit Eq. (2), aftr diiding it by n z 2 0, to b T u 1 1 l G l l GH fg u l GH l H l fh 1 2 fg 1 fh f whr G = n x / n z, and H = n y / n z. Now, th problm is to stimat roughly th alus of th paramtrs (l, f, G, H) such that Eqs. (3) and (4) ar clos to ach othr. Sinc only rough stimation is ndd, w first simplify (4) by assuming l = 1.0. Accordingly, th problm is rducd to finding th paramtrs (f, G, H) which satisfy 1 0 fg a b d 0 1 fh ~ b c 2 fg d f fh f whr ~ mans quals up to a scal. Lt b th hiddn unknown paramtr for this scaling. Thn, w ha 0 fg a b d 0 fh b c 2 fg d f fh f On solution to th abo quation for us as rough stimats of th paramtrs is: a c f d ; f ; G ; and H. (7) 2 f f A Lnbrg Marquardt procss is conductd finally to dri th prcis alus of (f, G, H), with th initial alus bing spcifid by (7) and th critrion bing to minimiz th alu of T u l G l l GH fg u l GH l H l fh 1 2 fg 1 fh f with rspct to all th pixls (u, ) on th lin imag I L. Aftr this optimization procss is don, th paramtr f of th camra modl is drid, complting th calibration procss. Four rsults of this calibration procss ar shown in Fig. 5. Th calibratd alus f for Figs. 5 and 5 ar and , rspctily, and thos for Figs. 5 and 5 ar and , rspctily. Th alidity of th proposd calibration mthod can b shown by th good fitnss of th bst-fitting llips to th manually-markd lin imag in ach cas, and th closnss of th calibratd alus f in th first two cass using a fishy-lns camra and in th rmaining two cass using a hyprbolic catadioptric camra. Fig. 5. Calibration rsults with yllow curs indicating manually-markd pixls, and rd llipss bing th bst-fitting rsults. Rsults using a fishy-lns camra with calibratd alus f bing and , rspctily. Rsults using a hyprbolic catadioptric camra with calibratd alus f bing and , rspctily. III. PROPOSED SPACE LINE DETECTION METHOD On of th important faturs in man-mad nironmnts is straight lin, and as formulatd by (2), ths spac lins ar

5 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 5 projctd by wid-angl camras to form conic sctions in th rsulting imag, calld th lin imags so far. In this sction, th proposd mthod for dtcting th conic-sction cur is dscribd, which, diffrntly from conntional mthods, gnrats qual-width rgions along a cur, as shown in Fig. 6. As a rsult, th proposd mthod can dtct thick curs in imags mor rliably, orcom th nois producd by dg dtction, and b utilizd in accordanc with th proposd camra modl (dscribd in Sc. II.B) for mor accurat dtction of parking-spac boundary lins. Fig. 6. An illustration of an qual-width cur along a cur F = 0 with width r, dfind to b th rgions of all th gray circls (not all drawn), or quialntly, th thick ara boundd by th two dashd curs. A. Proposd Dtction Mthod Th proposd spac lin dtction mthod is basd on th Hough transform with a nw cll accumulation schm to achi th ability to dtct qual-width thick curs. As dscribd by (2), a lin imag, which appars to b a conic sction in th acquird wid-angl imag, can b paramtrizd by th normal ctor (n x, n y, n z ) of th plan formd by th corrsponding spac lin and th origin of th camra. Th normal ctor can b xprssd as nx, ny, nz A, B, 1 A B whr A n x 2 x y z n n n, B n y 2 x y z n n n and 0 A, B 1. Th paramtrs (A, B) ar quantizd into nn alus to form Hough clls in this study, with th lin imags (conic-sction curs) corrsponding to th clls bing dscribd by th quation F(u, ) = 0 in (2), and th alus (n x, n y, n z) in (2) dfind by (9) and (10). Th first stp in th proposd dtction mthod is to obtain a binary rsion I b of th input wid-angl imag by dg dtction. Thn, for ach Hough cll at paramtrs (A, B) and for ach black pixl p in B with coordinats (u, ), if p is in th qual-width cur rgion of th lin spcifid by th paramtr (A, B), thn th cll alu at (A, B) is incrmntd by on. In mor dtail, by rfrring to Fig. 7, it can b figurd out that a pixl (u, ) is in th qual-width rgion with width r if and only if th cur F = 0 intrscts th circl C cntrd at (u, ) with radius r. Furthrmor, according to th intrmdiat alu thorm [16], th cur F = 0 intrscts th circl C if thr xists a point (u, ) = (u + u, + ) on C such that F(u, ) and F(u, ) ar with opposit signs. Accordingly, if F(u, ) is positi, w try to find th point (u, ) on C with th minimum alu of F(u, ), and thn dtrmin whthr F(u', ') and F(u, ) ar with opposit signs. Rrsly, if F(u, ) is ngati, w try to find th point (u, ) on C with th maximum alu of F(u, ), and thn dtrmin whthr F(u', ') and F(u, ) ar with opposit signs. For th first cas with F(u, ) 0, sinc F(u, ) should b th minimum alu and sinc th gradint F spcifis th dirction of incrasing th function alu F(u, ), th ctor (u, ) should b in th ngatd dirction of th gradint F. So, undr th constraint that th lngth of (u, ) is th radius r, th ctor (u, ) may b xprssd as [F(u, )/ F(u, ) ]r. For th scond cas with F(u, ) < 0, sinc F(u, ) should b th maximum alu, it can b drid by a similar rasoning that th ctor (u, ) should b with th sam dirction of th gradint F so that it can b xprssd as [F(u, )/ F(u, ) ]r. As a summary, w ha F u, r if F ( u, ) 0 u' u u u Fu, ' Fu, r if F ( u, ) 0 Fu, Accordingly, th function alu F(u, ) can now b drid by th 2 nd -ordr Taylor xpansion to b: T u 1 u u Fu ', ' Fu, Fu, HFu, 2 whr HF(u, ) is th Hssian matrix of function F dscribd by F F 2 u u HF F F 2 u whos dtails may b drid from (2) and ar omittd hr. F u, u', ' Fig. 7. An illustration for dtrmining whthr a pixl at (u, ) lis insid an qual-width cur or not. In conclusion, to dtct an qual-width lin in a binarizd wid-angl imag I b by th proposd Hough transform, w conduct th following procss. 1) For ach pixl p with coordinats (u, ) in I b and for ach Hough cll with paramtrs (A, B), calculat (u, ) and (u', ') by (11), and F(u, ) and F(u, ) by (2) and (12), rspctily. 2) If F(u, ) and F(u, ) ar with opposit signs, dcid th pixl p at (u, ) to b in th qual-width rgion of th lin spcifid by th paramtrs (A, B), and incrmnt th alu of th Hough cll with (A, B) by on. 3) Find out th paramtrs (A, B) of th dsird lin imags (conic-sction curs) from th rsulting Hough spac by th following stps. T

6 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 6 3.1) Enhanc th local maximums of th Hough spac by applying th following sharpning filtr: (14) ) Pick out all th Hough clls with alus largr than a pr-slctd thrshold and tak th clls paramtrs (A, B) for us as thos of th dtctd lin imags. 4) Us th drid paramtrs (A, B) to draw th conic sctions of th dtctd lin imags on th input imag as th output. By th way, th cur width r usd in (11) is dfind by considring th rror introducd in th dg dtction procss as wll as th rror introducd by th approximation of th paramtr l, as mntiond in Sc. II.B. Th formr is approximatd to b 1 pixl, and th lattr 1.2 pixls, according to th data shown in Fig. 4. As a rsult, th width r usd in this study is takn to b r = = 2.2 pixls. A rsult of th abo lin imag dtction mthod is shown in Fig. 8. Th input imag capturd by a hyprbolic catadioptric camra is shown in Fig. 8, with th Canny dg dtction rsult obtaind from it shown in Fig. 8. Th gnratd Hough spac is shown in Fig. 8, and th rsult of applying th filtr (14) in Fig. 8. Finally, som clls with largr alus wr pickd out, and th lin imags corrsponding to th clls paramtrs (A i, B i) wr drawn as shown in Figs. 14() and (f), whr th numbrs of drawn lins ar 30 and 50, rspctily. B. Effctinss of Proposd Cll Accumulation Schm As statd priously, ach Hough cll is spcifid by two paramtrs A and B, and corrsponds to a conic-sction cur F(u, ) = 0 in th input imag. Sinc th paramtrs A and B and th imag coordinats u and ar all quantizd to b discrt, th function alu F(u, ) for a crtain coordinat pair (u, ) may not b xactly zro. A conntional way to dal with this problm is to dfin a thrshold T and considr pixls with coordinats (u, ) satisfying th following inquality as bing on th conic sction dscribd by F(u, ) = 0: Fu, T. Two rsults yildd by this mthod ar shown in Figs. 9 and with diffrnt thrsholds T = 40 and 150, rspctily. As can b sn, th gnratd conic sctions ar not with qual widths. This phnomnon rsults from som undsirabl oprations which caus som dg pixls not blonging to th conic sction to b accumulatd into wrong Hough clls, and ic rsa. In contrast, th proposd mthod dscribd in Sc. III.A yilds qual-width curs as shown in Figs. 9 and for diffrnt cur widths r = 1 and 2 pixls, rspctily. Ths rsults show th capability of th proposd mthod for dtcting qual-width curs, which is suprior to conntional mthods and suitabl for applications rquiring highr lin dtction accuracy. Fig. 9. Comparison of conntional and proposd accumulation mthod. Non-qual-width rsults yildd by conntional mthod with thrsholds T = 40 and 150, rspctily. Equal-width rsults yildd by proposd mthod with width r = 1 and 2, rspctily. () (f) Fig. 8. Rsults of th proposd spac lin dtction mthod. Th input imag. Canny dg rsult. Th Hough spac. Th Hough spac aftr applid th filtr (14). ()(f) Rsults of 30 and 50 lins, rspctily. Som xprimnts wr also conductd to compar th spac lin dtction rsults yildd by th conntional Hough cll accumulation schm and thos by th proposd mthod. An input imag and th corrsponding Canny dg dtction rsult ar shown in Figs. 10 and, rspctily. Th 10 and 30 dtctd spac lin imags yildd by th conntional schm ar drawn in Figs. 10 and, rspctily, and thos yildd by th proposd mthod ar shown in Figs. 10() and (f),

7 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 7 rspctily. As can b found from th figurs, th curs dtctd by th conntional schm mostly go through th imag cntr, which ar not good rsults. This undsirabl phnomnon may b xplaind from th simulation rsults shown in Fig. 9. Spcifically, as can b sn from Fig. 9, th conntional schm gnrats a thickr cur whn th ral cur appars narr to th imag cntr, and ic rsa. This mans that ach Hough cll corrsponding to a cur narr to th imag cntr will collct ots from a thickr lin band in th input imag (i.., mor dg pixls will b accumulatd into such a cll), and ic rsa. Thrfor, whn using th conntional schm to dtct curs by picking up Hough clls with largr ots, thos curs narr to th imag cntr ar mor likly to b chosn first, yilding th rsults as shown in Figs. 10 and. In contrast, sinc th proposd mthod gnrats qual-width curs rywhr, this phnomnon dos not appar in th dtction rsults yildd by th proposd mthod as shown in Figs. 10() and (f). () (f) Fig. 10. Comparisons of spac lin dtction rsults yildd by conntional and proposd mthod. Input imag. Edg dtction rsult. 10 and 30 dtctd curs using conntional mthod. ()(f) 10 and 30 dtctd curs using proposd mthod. IV. DETECTION OF PARKING SPACE VACANCY Each parking spac is usually markd by som colord boundary lins. In this sction, som proprtis of such boundary lins ar first drid in Sc. IV.A. Thn, a mthod to dtct such boundary lins is proposd in Sc. IV.B. Finally, in Sc. IV.C, a mthod to mark th rgions of parking spacs using boundary lins, and a simpl acancy dtction mthod basd on background subtraction ar proposd, by which whthr a car is parkd in a parking spac can b dcidd. A. Proprtis of th Boundary Lins around Parking Spacs Thr proprtis of th boundary lins of parking spacs can b idntifid: (1) lying on th ground; (2) bing ithr paralll or prpndicular to on anothr; and (3) bing ignorabl if too far away from th camra. Ths proprtis ar discussd in mor dtail as follows. As statd in Sc. I, th wid-angl camras usd in th proposd parking lot systm ar affixd on th ciling to look right downward; so, th optical axis of th camra, namly, th Z-axis of th camra coordinat systm as shown in Fig. 2, is rtical with rspct to th ground spcifid as th XY-plan. Gin a boundary lin L 1 on th ground, its dirctional ctor (d 1x, d 1y, d 1z ) is paralll to th XY-plan, so w ha d 1z = 0. (16) Lt (A 1, B 1) b th Hough paramtrs of lin L 1 found by th spac lin dtction mthod proposd in Sc. III, and (n 1x, n 1y, n 1z) b th normal ctor of th plan formd by L 1 and th camra origin. Thn, from (9) w ha n1x, n1y, n1z A1, B1, 1 A1 B1. (17) In addition, sinc (n 1x, n 1y, n 1z) is prpndicular to th dirctional ctor (d 1x, d 1y, d 1z ) of L 1, w ha n, n, n d, d, d 0, (18) 1x 1y 1z 1x 1y 1z which, whn combind with (16) and (17), lads to Ad 1 1x Bd 1 1y 0, (19) so that th dirctional ctor (d 1x, d 1y, d 1z ) can b xprssd in trms of A 1 and B 1 as: d, d, d B, A,0. (20) 1x 1y 1z 1 1 Lt (A 2, B 2) b th paramtrs of anothr boundary lin L 2. Thn, th dirctional ctor (d 2x, d 2y, d 2z ) of L 2 can b drid similarly to b d2x, d2y, d2z B2, A2,0. (21) Now, sinc th two boundary lins L 1 and L 2 ar ithr paralll or prpndicular to ach othr, two cass can b idntifid. For th first cas whr th two boundary lins ar paralll, thir dirctional ctors satisfy d1x, d1y, d1z d2x, d2y, d2z, (22) which, whn combind with (20) and (21), lads to A1, B1 A2, B2, (23) whr is a scalar alu. For th othr cas whr th two lins ar prpndicular, th innr product of thir dirctional ctors satisfy d1x, d1y, d1z d2x, d2y, d2z 0, (24) which, with th us of (20) and (21), lads to A, B A, B 0. (25) 1 1 Moror, in ordr to ignor boundary lins which ar too far away, w chck th lation angl of ach boundary lin, which is dfind in a way as illustratd in Fig. 11 so that if th largr th angl is, th farthr th boundary lin is from th camra. According to our xprimntal xprinc, if th

8 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 8 camra is mountd at 2.5 mtrs high, th farthst usabl boundary lin is at a distanc about 10.0 mtrs from th camra. As a rsult, th maximum alu of is tan -1 (10.0/2.5) = 75.96, which is quialnt to n 1z sin() = Using this rsult with (17), w can dri anothr constraint on th paramtrs (A, B) as n 1z = 1 A1 B , or quialntly, as A1 B (26) Fig. 11. Dfinition of th latation angl of a boundary lin L 1. B. Automatic Dtction of Boundary Lins As can b sn from Figs. 8() and (f), th rsults of th lin imag dtction mthod proposd in Sc. III ar too noisy to b usd dirctly. In this sction, a mthod is proposd to mak us of th gomtric proprtis mntiond priously in Sc. IV.A to gnrat a bttr sgmntation rsult. As dfind abo, lt L 1 and L 2 b two boundary lins with paramtr pairs (A 1, B 1 ) and (A 2, B 2 ), rspctily. If (A 1, B 1 ) and (A 2, B 2) ar tratd as two ctors, thn if th two lins ar paralll to ach othr, (23) can b drid. Similarly, if th two lins ar prpndicular to ach othr, (25) can b drid. Rcalling that th boundary lins ar ithr mutually paralll or prpndicular, w dfin th dirction of th boundary lins in such a way that th paramtrs (A, B) of ach boundary lin ar ithr paralll or prpndicular to (cos, sin), i.., ar qual, up to a scalar, to ithr (cos, sin) or (cos(90 o +), sin(90 o +)). To find th corrct alu of th dirction, w first gnrat th Hough spac and apply th filtr as statd in Sc. III. From this Hough spac, about 0.3% of th Hough clls with th largst alus and satisfying (26) ar chosn and put into a st S. Also, w crat 90 bins in th rang 0 ~90 for diffrnt alus of. For ach cll with paramtrs (A i, B i) in th st S, w find th closst bin b i with alu i such that (A i, B i ) is ithr paralll or prpndicular to (cos i, sin i ), and incrmnt bin b i by th alu of th Hough cll with (A i, B i ). Aftr applying a Gaussian filtr with standard diation = 1, th bin with th largst accumulation alu is chosn to b th dirction of th boundary lins. An xprimntal rsult of th abo procss is dscribd in th following. An imag capturd by a hyprbolic catadioptric camra for us as th input is shown in Fig. 8. By following th lin imag dtction mthod proposd in Sc. III, th 2D Hough spac, aftr applying th filtr, bcoms as that shown in Fig. 8. Th rsults of th accumulatd bin alus of ar shown in Fig. 12, whr th largst bin is with alu = 76.5, which is takn finally as th dirction of th boundary lins. Aftr th dirction of th boundary lins is drid, th boundary lins which do not satisfy th dirction ar rmod as follows. For ach Hough cll in th st S with paramtrs (A i, B i), if thr xists a ral numbr offst within th rang 10 offst 10 such that th two ctors (A i, B i) and (cos( + offst), sin( + offst)) ar paralll or prpndicular to ach othr, thn th cll is considrd to satisfy th dirction and so kpt in th st S; othrwis, it is rmod. Aftrwards, th connctd componnts S i in th st S ar found according to th critrion that two clls with paramtr alus (A 1, B 1) and (A 2, B 2) ar connctd if A 1 A and B 1 B (27) Finally, th cntr of ach connctd componnt S i is calculatd and thir paramtrs (A i, B i) ar thn usd to spcify th boundary lins. By this procss, th rsult corrsponding to Fig. 12 is shown in Fig. 12, in which on can s that all th boundary lin of th parking spacs ha bn dtctd. Fig. 12. An xampl of parking spac dtction rsults with input imag shown in Fig. 8. Cll accumulation rsult of th dirction of boundary lins. Rsults of boundary lins found by proposd mthod, showing impromnt or lin dtction rsults shown in Figs. 8() and (f). C. Parking Spac Sgmntation and Vacancy Dtction Two mor stps ar proposd in this sction to sgmnt out th rgions of th parking spacs in th acquird wid-angl imag. Thn, a acancy dtction schm basd on background subtraction is adoptd. Ths thr stps ar dsignd to b prformd asily by a usr with no tchnical background, so that th ision-basd parking lot systm can b st up and utilizd connintly as claimd. Th first stp is to adjust th boundary lins manually by clicking on th imag to add and rmo boundary lin, on lin a tim. Th boundary lins ar first diidd into two mutually prpndicular groups, as shown in Fig. 13 and distinguishd by colors. Th usr may slct ithr group, and thn simply click on an xisting boundary lin to rmo it, or click on any othr position to add a nw boundary lin going through th mous position. It is important to not that, with th dirction found priously, th boundary lin can now b uniquly dtrmind with only on point markd by th usr; without, thr will b an infinit numbr of lins going through th point markd by th usr. For xampl, from th dtction rsults shown in Fig. 13, th rsult aftr two lins

9 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 9 addd and on lin rmod manually is shown in Fig. 13. Th scond stp is to find parking-spac rgions. In this stp, th usr may simply click on any position of a parking spac in th imag, and a rgion growing algorithm is prformd immdiatly to find th rgion of th parking spac using th boundary lins. Two rsults ar shown in Figs. 13 and. Fig. 13. Parking spac sgmntation. Boundary lins dtctd by proposd mthod ar diidd into two groups markd by rd and blu, rspctily. Boundary lins aftr manually adjustd. Rgions of two grn-markd parking spacs found automatically by proposd schm. Th final stp is to find acant parking spacs. To implmnt this, th usr has to captur bforhand an imag of ach parking spac whn it is acant, and considr th imag as th background of th parking spac. Subsquntly, to dtrmin th acancy of th parking spac, ach pixl in th acquird wid-angl imag is considrd as a forground pixl if th absolut diffrnc btwn th pixl s alu and that of th background pixl is largr than a thrshold alu in at last on of th R, G, and B channls. And thn, if th numbr of forground pixls is largr than 20% of that of th pixls in th parking-spac rgion, th parking spac is considrd to b occupid; othrwis, acant. An xprimntal rsult is shown in Fig. 14. A ral indoor ision-basd parking lot systm implmntd in this study is dscribd latr in Sc. V.D. V. EXPERIMENTAL RESULTS AND DISCUSSIONS Exprimnts ha bn conductd to dmonstrat th corrctnss, fasibility, and robustnss of th proposd mthod. Som rsults and discussions ar prsntd in this sction. A. Exprimntal Rsults of Proposd Calibration Mthod Th proposd camra calibration mthod dscribd in Sc. II uss th imag of only a spac lin, without knowing its position or dirction, to dri th paramtrs of th proposd gnral modl for fishy-lns, parabolic catadioptric, and hyprbolic catadioptric camras. By assuming that th imag cntr has alrady bn calibratd by th us of th circular boundary of th omni-imag as don in [11] and [15], th ffcti focal lngth alu f is th only rmaining on to b calibratd. For this, a sris of xprimnts wr conductd using spac lins lying on th ground at diffrnt positions, with th camra affixd on th ciling and looking downward. Spcifically, as illustratd in Fig. 15, on of th paramtrs of a spac lin L is its lation angl, so sral simulatd spac lins with diffrnt lation angls in th rang of 0 ~90 wr gnratd for uss in th xprimnts. Th paramtrs f of ths simulatd lins wr all st to b f = 500, and thir lin imags gnratd to b of th siz idntically. Also, th coordinats of th pixls on ach lin imag wr disturbd by Gaussian nois with zro man and arying standard diations Thn, th proposd calibration mthod was applid to dri th paramtr f using ths simulatd lin imags. This procss was rpatd 100 tims, and th man and ariancs of th drid alus of f ar plottd in Figs. 16,, and for diffrnt nois lls = 1.0, 3.0, and 5.0 pixls, rspctily. Rcalling that th actual alu of th paramtr f is f = 500, on can s from th figurs that th paramtr f can b robustly calibratd undr a larg nois ll whn th lation angl > 15. Not also that a spac lin with an lation angl nar 0 will appar to b a short and narly straight lin sgmnt going through th imag cntr, so that th paramtr f cannot b calibratd rliably using it, as xpctd according to th thory of th proposd calibration mthod dscribd in Sc. II.C. Fig. 15. Dfinition of th latation angl of a spac lin L on th ground. Fig. 14. Parking spac acancy dtction. Input imag. Vacant parking spacs markd as grn rgions. B. Calibration of Camra Paramtrs Th main objcti of th proposd mthods is th as for a non-tchnical usr to st up th systm. In this sction, achimnt of this goal is dmonstratd th usr only has to slct a singl spac lin with its position and dirction unknown. Imags lik thos shown in Fig. 17 wr capturd by a hyprbolic catadioptric camra with MapCam MRC530N

10 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 10 manufacturd by ERis, Inc. Four xprimntal rsults ar shown in Figs In ach xprimnt, th usr only has to choos arbitrarily an obious spac lin in th capturd imag, and markd roughly th pixls on th lin as yllow points by mous dragging. Thn, th proposd calibration mthod was applid to dri th alu of th ffcti focal lngth f using th yllow points. Th alus of f so drid for th cass shown in Figs. 17- ar , , , and , rspctily, and th bst-fitting llipss to th markd spac lins ar shown in rd. With paramtr f = , th boundary lins of th parking spacs wr finally found and drawn in Fig. 17() using th proposd dtction mthod. Also conductd wr similar xprimnts with a fishy-lns camra manufacturd by Hunt Elctronic, Inc. with modl No. HLC-1NAD, and th rsults ar shown in Fig. 18. Th rsults of both xprimnt sris show th fasibility and robustnss of th proposd calibration mthod by th fitnss of th drawn rd llipss to th markd yllow points, th closnss of th calibratd alus f to th ral alu, and th narly prfct orlapping of th drawn boundary lins on th ral ons. four imags wr firstly drid. Thn, th boundary lins wr dtctd automatically and suprimposd on th original imags as shown in Figs. 19-, rspctily. From th figurs, on can s that th boundary lins fit wll to th ral ons apparing in th capturd imags, maning that th dirctions of th boundary lins wr found corrctly by th proposd mthod. () Fig. 17. Applying proposd calibrat mthod to dri th paramtr f of a hyprbolic catadioptric camra. - Four rsults with calibratd alus f = , , , and , rspctily. () Boundary lins found by th proposd dtction mthod with f = Fig. 16. Computd mans and ariancs of calibratd alus f for simulatd spac lins with diffrnt lation angls whr standard diaion of Gaussian nois is 1.0 pixl for, 3.0 pixls for, and 5.0 pixls for. C. Exprimntal Rsults of Boundary Lin Dtction In th boundary lin dtction mthod proposd in Sc. IV.B, th dirction of th boundary lins, dnotd as, is computd first and th boundary lins ar drid accordingly. Som xprimnts wr conductd to tst th capability of this schm of finding as dscribd nxt. First, an imag of an indoor parking lot was capturd by a hyprbolic catadioptric camra, as shown in Fig. 19. Thn, this imag was rotatd through th angls 30, 60, and 90 as shown in Figs. 19, and, rspctily. Th boundary lin dirctions in ths () Fig. 18. Us of proposd calibration mthod to calibrat a fishy-lns camra. - Four rsults with calibratd alus f = , , , and , rspctily. () Th boundary lins found by proposd dtction mthod with f =

11 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 11 To dmonstrat that th dirction of th boundary lins can b robustly found n undr bad conditions, two mor xprimnts wr conductd with input imags shown in Figs. 20 and, in which nois was prsnt, cars wr parkd in th spacs, and th lighting situations wr poor. Th rsults of th first xprimnt ar shown in Figs. 20, (), and (g), and thos of th scond ar shown in Figs. 20, (f), and (h). Spcifically, th dg dtction rsults ar shown in Figs. 20 and, rspctily, in which on can s that th boundary lins wr poorly dtctd; also, som of th boundary lins ar missing, as shown in Figs. 20() and (f). Howr, th dirctions of th dtctd and drawn boundary lins ar corrct, maning that th dirction can b drid prcisly n undr bad conditions. With this corrct alu of, th boundary lins can b adjustd asily by th proposd mthod as dmonstratd by th rsults shown in Figs. 20(g) and (h). shown in Fig. 21 as background, th systm stup procss was compltd, and parking spac acancy dtction was startd. In on of th xprimnts w conductd, this systm was maintaind to run for 24 hours to dtct acant parking spacs ry minut. Th rsulting dtction accuracy was 99.67%, which is good nough for ral applications. Fig. 19. Automatic dtction rsults of boundary lins. Rotation angls of ths imags ar 0, 30, 60, and 90, rspctily. Th dtctd boundary lins ar drawn and suprimposd on th imags. () (f) D. Stup of a Ral Vision-basd Indoor Parking Lot Systm A ral indoor ision-basd parking lot systm was stablishd and its us for this study is introducd in this sction. A fishy-lns camra manufacturd by Hunt Elctronic with modl No. HLC-1NAD was affixd on th ciling of th parking lot. An imag as shown in Fig. 21 was acquird at midnight firstly and usd both for calibration and for dtcting th boundary lins of th parking spacs. Spcifically, a spac lin in th imag was chosn arbitrarily according to a rul of thumb that th lin should b long nough and not straight. Th lin pixls wr tracd and markd in yllow as shown in Fig. 21, by which th paramtr f was calibratd to b Aftrwards, th dirction of th boundary lins was drid, and th boundary lins dtctd automatically, with th rsults drawn in Fig. 21. Subsquntly, boundary lins wr addd or rmod by singl clicks on th imag as dscribd priously. A rsult of such adjustmnts is shown in Fig. 21. At last, th parking spacs wr sgmntd out by clicking on any point within th rgion of ach spac and applying a rgion growing algorithm. Th rgions of two parking spacs so found and drawn in grn ar shown in Figs. 21() and (f), rspctily. Aftr using th capturd imag (g) (h) Fig. 20. Rsults of two xprimnts undr bad conditions with thos of th first shown in ()(g), and thos of th scond shown in (f)(h). Input imags. Edg dtction rsults. ()(f) Automatic dtction rsults of boundary lins. (g)(h) Adjustd boundary lins. VI. CONCLUSIONS AND FUTURE WORKS A connint indoor ision-basd parking lot systm has bn proposd in this study, which is asy to st up by a typical usr with no tchnical background and can dtct acant parking spacs automatically. Th systm uss wid-angl camras, lik fishy-lns or catadioptric ons and analyzs parking-spac boundary lins basd on a nw camra modl proposd in this study. This modl approximats optimally on of th paramtrs usd in a conntional modl (th distanc l from th ffcti iwpoint O to th pinhol point O c ) whil rsring som important charactristics of lin imags, including th shap of th cur and th locations of th anishing points. A nw lin-basd calibration mthod has also bn proposd to calibrat th camra modl using only on

12 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 12 spac lin without knowing its location and dirction, so that th calibration procss can b don asily by a usr without any tchnical background. A nw Hough transform has bn proposd as wll to dtct spac lins, in which a skillful cll accumulation schm is usd to gnrat qual-width curs, yilding mor robust and accurat dtction rsult of parking-spac boundary lins. A connint adjustmnt mthod has also bn dlopd such that a usr can add or rmo boundary lins by simpl clicks on input imags. Currntly, th background imags should b larnd for arious lighting conditions in ordr to conduct parking-spac acancy dtction basd on background subtraction. Mor intllignt mthods may b dlopd to rmo this waknss in th futur study. [6] S. Ramalingam, P. Sturm, and S. K. Lodha, Gnric Slf-Calibration of Cntral Camras, Computr Vision and Imag Undrstanding, ol. 114, no. 2, pp , [7] S. Gasparini, P. Sturm, and J. P. Barrto, Plan-Basd Calibration of Cntral Catadioptric Camras, Proc. IEEE 12th Intrnational Confrnc on Computr Vision, pp , [8] C. Gyr and K. Daniilidis, A Unifying Thory for Cntral Panoramic Systms and Practical Implications, Proc. Sixth Europan Conf. Computr Vision, pp , [9] X. Ying and Z. Hu, Catadioptric Camra Calibration Using Gomtric Inariants, IEEE Trans. Pattrn Analysis and Machin Intllignc, ol. 26, no. 10, pp , [10] X. Ying and Z. Hu, Can W Considr Cntral Catadioptric Camras and Fishy Camras within a Unifid Imaging Modl? Proc. Europan Confrnc on Computr Vision, pp , [11] X. M. Dng, F. C. Wu, and Y. H. Wu, An Easy Calibration Mthod for Cntral Catadioptric Camras, Acta Automatica Sinica, ol. 33, no. 8, pp , [12] Y. Bastanlar, L. Puig, P. Sturm, J. J. Gurrro, and J. Barrto, DLT-Lik Calibration of Cntral Catadioptric Camras, Proc. 8th Workshop on Omnidirctional Vision, Camra Ntworks and Non-classical Camras, Oct [13] C. Gyr and K. Daniilidis, Catadioptric Projcti Gomtry, Int l Journal of Computr Vision, ol. 45, no. 3, pp , [14] J. P. Barrto and H. Araujo, Gomtric Proprtis of Cntral Catadioptric Lin Imags, Proc. Snth Europan Confrnc on Computr Vision, pp , [15] J. Fabrizio, J. P. Tarl, and R. Bnosman, Calibration of Panoramic Catadioptric Snsors Mad Easir, Proc. IEEE Third Workshop on Omnidirctional Vision, pp , [16] T. Apostol, Calculus, Vol 1: On-Variabl Calculus with an Introduction to Linar Algbra, Wily, 2 nd dition, Jun, Shn-En Shih rcid th B.S. dgr in computr scinc from National Chiao Tung Unirsity, Taiwan, in 2009, and is currntly pursuing th Ph.D. dgr at th Collg of Computr Scinc, National Chiao Tung Unirsity. H has bn a rsarch assistant at th Computr Vision Laboratory in th Dpartmnt of Computr Scinc at National Chiao Tung Unirsity from August His currnt rsarch intrsts includ computr ision, imag procssing, human-machin intrfacing, and stro ision. () (f) Fig. 21. Stps of stting up proposd systm. An imag capturd at midnight. Manually-markd pixls (in yllow) of a spac lin for calibration task. Rsults of automatic dtction of boundary lins. Rsult of boundary lin adjustmnt. () and (f) Rgions of two found parking spacs (markd in grn). REFERENCES [1] K. Blumr, H. R. Halash, M. U. Arsan, H. Dong, and N. Maridis, Cost-Effcti Singl-Camra Multi-Car Parking Monitoring and Vacancy Dtction towards Ral-World Parking Statistics and Ral-Tim Rporting, Proc. Nural Information Procssing, pp , [2] C. C. Huang and S. J. Wang, A Hirahical Baysian Gnration Framwork for Vacant Parking Spac Dtction, IEEE Transactions on Circuits and Systms for Vido Tchnology, ol. 20, no. 12, pp , [3] H. Ichihashi, T. Katada, M. Fujiyoshi, A. Notsu, and K. Honda, Impromnt in th prformanc of camra basd hicl dtctor for parking lot, Proc IEEE Intrnational Confrnc on Fuzzy Systm, pp , [4] W. Lixia and J. Dalin, A Mthod of Parking Spac Dtction basd on Imag Sgmntation and LBP, Proc. Fourth IEEE Intrnational Confrnc on Multimdia Information Ntworking, pp , [5] X. Dng, F. Wu, Y. Wu, L. Chang, W. Liu, and H. Wang, Calibration of Cntral Catadioptric Camra with On-Dimnsional Objct Undrtaking Gnral Motions, Proc. 18th IEEE Intrnational Confrnc on Imag Procssing, pp , 2011 Wn-Hsiang Tsai rcid th B.S. dgr in EE from National Taiwan Unirsity, Taiwan, in 1973, th M.S. dgr in EE from Brown Unirsity, USA in 1977, and th Ph.D. dgr in EE from Purdu Unirsity, USA in Sinc 1979, h has bn with National Chiao Tung Unirsity (NCTU), Taiwan, whr h is now a Chair Profssor of Computr Scinc. At NCTU, h has srd as th Had of th Dpt. of Computr Scinc, th Dan of Gnral Affairs, th Dan of Acadmic Affairs, and a Vic Prsidnt. From 1999 to 2000, h was th Chair of th Chins Imag Procssing and Pattrn Rcognition Socity of Taiwan, and from 2004 to 2008, th Chair of th Computr Socity of th IEEE Taipi Sction in Taiwan. From 2004 to 2007, h was th Prsidnt of Asia Unirsity, Taiwan. Dr. Tsai has bn an Editor or th Editor-in-Chif of sral intrnational journals, including Pattrn Rcognition, th Intrnational Journal of Pattrn Rcognition and Artificial Intllignc, and th Journal of Information Scinc and Enginring. H has publishd 157 journal paprs and 245 confrnc paprs and rcid many awards, including th Annual Papr Award from th Pattrn Rcognition Socity of th USA; th Acadmic Award of th Ministry of Education, Taiwan; th Outstanding Rsarch Award of th National Scinc Council, Taiwan; th ISI Citation Classic Award from Thomson Scintific, and mor than 40 othr acadmic papr awards from arious acadmic socitis. His currnt rsarch intrsts includ computr ision, information scurity, ido surillanc, and autonomous hicl applications. H is a Lif Mmbr of th Chins Pattrn Rcognition and Imag Procssing Socity, Taiwan and a Snior Mmbr of th IEEE.