Target Detection Algorithm Based on the Movement of Codebook Model

Transcription

1 Copuer and nforaon Scence Vol. 5 No. ; March 01 Targe Deecon Algorh Based on he Moveen of Codebook Model Kage Chen Xaojun Han & Tenghao Huang College of Elecronc and nforaon Engneerng Tanjn Polyechnc Unversy Tanjn Chna E-al: hanxaojun_j@16.co Receved: Deceber Acceped: Deceber Publshed: March 1 01 do: /cs.v5np49 URL: hp://dx.do.org/ /cs.v5np49 Absrac Moveen arge deecon s he researchful ephass and apora n he felds of copuer vson odel recognon and vdeo codng. n order o exrac ovng arges fro he coplex background scenes hs paper pus forward o calculae he color dsoron degree by eans of geng every pxel or a group of pxels of e seres odel and converng pxels fro RGB space o HSV space. Based on he background Codebook odel of he arge oon deecon algorh he experen shows ha he ehod can acheve beer arge deecon qualy. Keywords: Codebook Moon arge deecon Copuer vson Dsoron degree 1. nroducon Wh he developen of copuer echnology usng copuer o realze he huan vsual funcon hrough a copuer has becoe one of he os popular subjecs n copuer feld. One poran aspec of copuer vson research s oon arge deecon. can be wdely appled n he felds of nellgen vdeo onorng huan-copuer neracon vrual realy robo navgaon raffc deecon and any oher areas. Lgh flow ehod (McKenna Seal e al. 000) s rarely used because of he copuaonal coplexy and frae dfferenal ehod can deal wh he slow background change. However he deeced objecs easly appear so rupure and epy ha he coplee oon arge s hard o ge. Therefore people end o use he ehod of reducng background ore and ore. A presen he proble on ovng arge deecon has no been solved copleely n coplex envronen. Ths s anly because he background changes happen a any e wheher ndoors or oudoors ncludng llunaon change background dsurbance and he background change caused by he oon arge self ec. Meanwhle here are soe shorcongs of he presen algorh n background renewal speed hreshold selecon flexbly eory sorage and accuracy. For exaple fne dfference ehod (C. Bregler 1997) and ean fler ehod (C. Wren e al. 1997) call for large sorage space and have poor adapve ably. And he unodal dsrbuon odel (D. Koller e al. 1993) canno odel he background of he shakng ree branches. Alhough gaussan xure odel can be appled n background odelng wh coplex or dynac background nose(such as he background randrops and he shakng ree branches) s dffcul o use several led gaussan odel o descrbe he rapdly changng background accuraely. And s hard o keep he learnng effcacy of gaussan xure odel n an deal sae. Based on he above reasons hs paper proposes he fuure nspecon ehod on he bass of Codebook fne dfference ehod whch copares he color dsoron by converng pxels fro RGB space o HSV (hue sauraon value) space. And hrough HSV color saplng sudy on hree axs every pxel can ge a code book. Accordng o he dsrbuon characerscs of he prospecs and background pons n he age pon he background code words are separaed and can be used for background odelng. The resuls show ha alhough he converson o HSV color odel nroduces floang pon arhec whch akes he processng speed slower copared o he ehod of K (K K e al. 004) ore accurae deecon effec can be obaned ha he foreground objecs of he coplex background can be deeced successfully.. Codebook Background Model Codebook odel algorh s o oban each pxel yards based on he color sandard and brghness boundares Publshed by Canadan Cener of Scence and Educaon 49

2 Copuer and nforaon Scence Vol. 5 No. ; March 01 cluserng by eans of usng quanave and cluserng echnques o buld background odel and ranng each pxel. Each pxel has a dfferen codebook each codebook conans several code words and all he pxels of codebook ake up he codebook odel. f X x1 x x N s he sequence saple value of a pxel aong whch x (=1 N ) s RGB vecor. f C c 1 c c L s he codebook of hs pxel each code word x (=1 L ) s defned as bnary group n ax v R G B u f p q aong whch n ax and s he correspondng srucure pxel nu and axu brghness values of he code words. f can show he frequency of he codebook and can show he axu e nerval of he code words. Besdes p and q can be used o show he achng e of he frs and las e afer s appearance whch can be se as a sple frae. n he process of ranng he nal Codebook Le X s defned as a sngle pxel conssng of N RGB-vecors: X x x 1 x N. Every saple value x represens he saple a he oen of. can be copared o he presen yard so as o deerne whch yard c can be ached wh. Then he achng yard s used as code esae of he saple. n order o asceran he bes ach of he yard he color dsoron and brghness are used as he reference for he easure boundary. When pxel saple values surpass he exsng Codebook border new Codebook enry s creaed. And when he pxel value s n he exsng border area he code saple border wll ncrease. However f a pxel s beyond he boundary dsance of he code saple a new code enry s creaed and a hgh or low hreshold s se. And every code enry s exaned o check wheher pxel s n he code border. Besdes f hs pxel value s whn he border he axu and nu hreshold s adjused o ake sure s ncluded n he code border. Meanwhle he las updaed e s se as he curren e and he sascs access frequency of each code e s esaed. n addon when he code canno be assessed for a long e ay be due o he nose or ovng prospec arge. As e goes on becoes an old code. Therefore s necessary o updae he needed enry codebook and delee he unwaned enry code. The an seps of he algorh (A. Elgaal e al. 000) are descrbed as: Ⅰ. Se L 0 c ; Ⅱ. FOR 1 TO NDO ⅰ. x R G B ⅱ.Search code R G B (1) c n C c L 1 o ach he saple x o sasfy: colords x v brghness boundary color dsance 1 n ax brghness boundary brghness ure ⅲ. f c canno fnd he ached code L 1. L and a new code enry c s added: v L R G B u L 1 1 ; () ⅳ. Updaed achng code c ncludes: Updang ax u f p q n and v R G B : v f R R f 1 f G G f 1 f B B f 1 n ax ax f 1 ax q p u n (3) END FOR Ⅲ. For every code c 1 L : se ax N q p 1 (4) 50 SSN E-SSN

3 Copuer and nforaon Scence Vol. 5 No. ; March 01 Ⅳ. Usng o elnae redundan code words he accurae and nal codebook wh he represenave background s found ou M (K s he ndex of code word): M c k ck C k TM. Seps n he algorh 1 s global hreshold varable whch us ake suable adjusen for he applcaon. Threshold TM usually ake half he nuber of fraes naely N / all he code words wh he represenave background us appear whn he frae. Aong hese he condons of sepⅡ are ha he colors of x and c are very slar and ha he brghness of x us be whn he accepable brghness of c. Here s necessary o fnd he code word ha akes he frs condon sasfy he second condon. The reason of nroducng e rule s ha redundan codes are obaned n he process of ranng aong whch soe represen he prospec ovng arge and nosy code words. Usng sep Ⅳ can separae hese code words n probably sense whch allows he exsence of ovng arge n he nal ranng process. 3. Deernng he Scope of Color Dsoron Degree and Brghness Degree n order o deal wh he llunaon changes of shadows and hghlghs RGB odel s ofen used. Bu s bad for he color effec of he dark areas because he pxel dfferences n he dark areas have hgher sably han ha n he brgh areas. For exaple L and D represen he wo dark pxels and a lgher pxel hen her color dsoron degree (CDD) s calculaed respecvely as shown n Table 1. Fro Table 1 we can see ha he color change s larger n low lgh han ha n hgh lgh. Thus hgh brghness of he deecon sensvy wll be sacrfced. Theorecally RGB color space has bgger dfferences han eye percepon whle HSV color space s conssen wh huan eye percepon characerscs and has been wdely used n he vdeo age rereval. Through HSV color space huan eyes can have he separae percepon of he color change. And he perceved color dfference s proporonal o he aoun of Eucld dsance. Therefore hs paper wll calculae he color dsoron degree by converng pxels fro RGB space o HSV space so as o judge he changes beween prospec pxel and background pxel (Greffenhagen M. e al. 000) aglely. Suppose a funcon RGBHSV ( ) whch s convered pxel RGB value o HSV value h s v are hree vecors n 0 01 v 01.For pxel x R G B y R G B. HSV color odel h s RGB HSV p RGBHSV p x colords ( x y ) and y p. s snp. h p. s snp. h p. s cosp. h p. s cosp. h p. v p. v (5) n order o defne dark and hghlgh areas s necessary o defne he brghness change range of he ovng arge. And for each code word s scope s defned as low h : ax low n n ax h (6) Aong he he saller s he greaer he brghness range s he range of he code s sable n he process of updang. Brghness funcon s defned as brghness ure low false x n ax h (7) ohers 4. The Prospec of Moveen Targe Deecon Based on Codebook For deecon echnology o reduce background oon he os drec ehod s o subrac he curren frae fro he background odel. Ths paper wll judge wheher pxel saplng value aches wh he correspondng code. f hey ach he pon s aken as he background pon. Oherwse s aken as he prospec pon. For Publshed by Canadan Cener of Scence and Educaon 51

4 Copuer and nforaon Scence Vol. 5 No. ; March 01 he new npu pxel x R G B and he correspondng code M n he process of oveen arge deecon reducng background operaon algorh BGS (x) s shown n Fgure Updang he Background Model n he Tesng Process n order o be suable for he real-e accuracy of he vdeo onorng syse updang he code s necessary n he process of arge deecon. Much aenon should be pad o llunaon change and ovng arge self (such as sop or raffc) caused by he changes of he background odel updang. And ncludes wo pars naely he background areas and he coverage areas of he frae objec. f he saple value of a pxel canno ach wh he presen code M a new code word wll be creaed. Frs updang he background pxel and fndng he new npu pxel x R G B ached wh code word n ax c fro M hen updang u f p q v R G B o u n n ax ax and f 1 ax q p v ( f R R ) ( f 1) ( f G G ) ( f 1) ( f B B ) ( f 1) (8) A he sae e a frae for ovng objecs coverage area s consdered. The updang ehod wll ncorporae no he background odel a hgh updang rae and updae he ached code words c u and v R G B o v u ( f R R) ( f ) ( f G G ) ( f ) ( f B B) ( f n ax n ax f 1 ax q p (9) 6. Analyzng Experenal Resuls n order o evaluae he proposed algorh Vsual C++6.0 and open source achne vson lbrary OpenCV1.0 are used. And n order o deec he prospec arge a seres of vdeos realze he background odelng and background odel s regularly updaed. Moreover he resuls show ha as o oudoor vdeo every pxel needs an average sx yards o ge background odel whle ndoor vdeo jus needs one or wo background value. Ths algorh needs o be raned once and he repeaed ranng canno enhance he deecon ably. And he e sandards can be used o dsngush he code words havng real background fro he ovng foreground code words. And akes no dfference beween consderng he frequency f and of he code words and only consderng he nspecon ably of. The experenal resuls are obaned afer he sple orphology processng by usng he algorh for a group of ndoor and oudoor vdeos. They are shown as Fgure and Fgure 3. Paraeer sengs n he experenal process are shown n Table. are hreshold varables and are brghness coeffcens N s for ranng he frae n Table 1 nuber. n he process of background odelng he exsence of he ovng arge canno be allowed o sore he prevous pxel nuercal value so he sall eory s needed. Fro above we can see ha because he brghness and color dfference are consdered n he ehod of hs paper he dark and hghlgh areas are deal wh effecvely. 7. Concluson n hs paper adapve background nus algorh s used o oban effecve background odel hrough sple ranng whch can l he sze of he eory used and can be well adaped o he background oveen and lgh changes. Because he color dsoron s copared by converng he pxel fro RGB space o HSV space ore accurae arge deecon effec s acheved han he ehod of K. However due o he nroducon of floang pon arhec he algorh processng speed s becong slower. Therefore n he fuure research ore aenon should be pad on he led sraegy of he code sze and he orderng sraegy of he code words whch can reduce he eory ach he e of he codebook and furher prove he processng speed. References A. Elgaal D. Harwood & L. S. Davs. (000). Non-paraerc odel for backgroun subracon. n proceedngs of European Conference on Copuer Vson C. Bregler. (1997). Learnng and recognzng huan dynacs n vdeo sequences. n Proceedngs of EEE ) 5 SSN E-SSN

5 Copuer and nforaon Scence Vol. 5 No. ; March 01 CVPR hp://dx.do.org/ /cvpr C. Wren A. Azarbayejan T. Darrell & A. Penland. (1997). Pfnder: Real-e rackng of he huan body. EEE Transacons on Paern Analyss and Machne nellgence 19(7) hp://dx.do.org/ /afgr D. Koller K. Danlds & H. H. Nagel. (1993). Model-based objec rackng n onocular age sequences of road raffc scenes. nernaonal Journal of Copuer Vson 10(3) Greffenhagen M. Raesh V. Coancu D. e al. (000). Sascal odelng and perforance characerzaon of a reale dual caera survellance syse. EEE CVPR hp://dx.do.org/ /cvpr K K. Chaldabhongse T. H. Harwood D. e a1. (004). Background odelng and subracon by codebook consrucon. Proc. n. Conf. age Processng Sngapore hp://dx.do.org/ /cp McKenna Seal. (000). Trackng groups of people. Copuer Vson and age Undersandng 80(1) Table 1. Color dsoron degree L(RGB) D(RGB) CDD (101010) (8101) 4/30 (000000) (198000) 4/600 Table. Paraeer seng 1 N Publshed by Canadan Cener of Scence and Educaon 53

6 Copuer and nforaon Scence Vol. 5 No. ; March 01 Le ached = 0 and gve he hreshold varable o Ener he new pxel x calculae brghness R G B no ached=0 colords x y n brghness ure ax no yse ached=1 no x s foreground pxel ached=0? yes x s background pxel Wheher all judgen? yes reurn Fgure 1. Flow char of algorh a. oudoor vdeo screensho b. oudoor arge deecon resuls Fgure. Oudoor conras experen resuls a. ndoor vdeo screensho b. oudoor arge deecon resuls Fgure 3. ndoor conras experen resuls 54 SSN E-SSN