Pht hin, phn loi v theo di i tng chuyn ng trong h thng gim st thng minh

Pht hin, phn loi v theo di i tng chuyn ng trong h thng gim st thng minhTIU LUN TNG QUANChuyn ngnh: C S TON HC CHO TIN HCM s: 62.46.01.10NCS. NGUYN VN CNNi dung trnh byPhn m ut bi tonTnh hnh nghin cu trong v ngoi ncMt s phng php, thut ton s dngPhn kt lunPhn 1Phn m u1. L do chn vn nghin cu Lun vn tin s: Nghin cu mt s thut ton xc nh mt phng tin giao thng trong video giao thng.Video giao thng => h thng giao thng thng minh Phng tin giao thng=>xe t, m t, xe my, ngi i b.Xc nh mt => m s lng phng tin => Pht hin, phn loi, theo di, thc hin m.2. Mc ch nghin cuTrn c s tm hiu bi ton Pht hin, theo di, v phn loi i tng chuyn ng;Trn c s tm hiu nhng nghin cu trc y trong v ngoi nc v vn ny;Tin hnh thng k, phn tch phng php, thut ton, kt qu t cNhng vn c th ci tin, khc phc hn ch, xut mt s ci tin, phng php mi nng cao chnh xc, tc x l ca thut ton.3. i tng nghin cuBi ton pht hin, theo di v phn loi i tng chuyn ng.Cc cng trnh v ang nghin cu trong v ngoi nc v vn pht hin, theo di v phn loi i tng chuyn ng.Cc thut ton, phng php p dng trong vn ny.

4. Phm vi nghin cu:Bi ton lin quan n video quay ch OutdoorQu trnh x l hnh nh v a ra thng tin.Phn tch video thnh cc khung hnh. Pht hin i tng chuyn ng trong cnh video.Phn loi da vo cc c trng hnh hc, chuyn ng.Theo di chuyn ng da vo c tnh khng gian, thi gian.5. Phng php tin hnhBc 1: Su tp ti liu Bc 2. Phn tch cu trc mt h thng; Thng k, phn tch v nh gi cc phng php s dng; Kt hp mt s thuc tnh, phng php gii quyt chnh xc v tc .Bc 3. Xy dng chng trnh thc nghim.Bc 4. nh gi v hiu chnh thut ton v chng trnh.

Phn 2t bi ton

Lnh vc nghin cuNhn dng nh l cng on cui cng v quan trng trong h thng x l nhD liu u vo l video.

Khung khai ph d liu videoD liu u ra l d liu i tng quan tmNhn dng videoThu nhn videoNn d liu videoTin x lTch nnPhn onPhn loiTheo diPht hinLnh vc nghin cu lin quan

ng dng ca nhn dng nh v video trong thc tSurveilance: gim stAutonomous navigation: chuyn hng t ngRobot guidance: Hng dn robot Industrial inspection: Kim duyt cng nghip Microscopy: Knh hin vioceanography: Hi dng hcUltrasonic imaging: siu m Hnh nh aerial reconnaissance & mapping: My bay trinh stRadiology: X-Quangv lp bn Astronomy: Thin vn hcradar: Ra aMeteorology: kh tng hcremote sensing: Vin thmSeismology: a chn hcParticle physics: Vt l htH thng gim st thng minh l g?L mt h thng:u vo: video, hnh nh, m thanh thu c t nhng ni cn gim st v ti thi gian xc nh.u ra: Ti khong thi gian xc nh ci tng chuyn ng v khng chuyn ng.Nn nh tnhi tng chuyn ngLoi i tng chuyn ng. t, xe my, ngi i b v phng tin khcChuyn ng ca i tng nh th no. Vn tc, qu oH thng gim st thng minh bao gm:

Object DetectionObject ClassificationObject TrackingPhn tch bi ton nhn dng videoBi ton 1: Pht hin cc i tng chuyn ng Tch cc i tng chuyn ng ra khi cc khung hnh.Phng php thng c s dng: Phng php tr nh nn, Phng php da trn thng k,Phng php chnh lch tm thi, Phng php da trn lung th gic.Bi ton 2: Phn lp i tngPhn loi ra cc lp i tng c nh ngha trc: Lp ngi, lp phng tin, lp ng vt, C hai hng chnh tip cn: Da trn hnh dng Da trn chuyn ng ca cc i tng. Bi ton 3: Theo di i tng a ra chui cc hnh vi ca i tng.ng i ca i tng, Tc hay hng chuyn ng ca i tng.

Bi ton 1Pht hin cc i tng chuyn ngS khi qut h thng pht hin i tng

Pht hin cc vng nh niCc phng php tr nh nn Background SubtractionCc phng php da trn thng k Statistical MethodsCc phng php da trn s chnh lnh tm thi gia cc khung hnh Temporal Differencing

X l cc vng nh niTin x l mc im nh ni Loi b nhiu, pht hin v loi b bng, Phn tch lin kt cc khi: Lin kt cc vng im nh thnh cc khiTin x l cc vng nh ni: Kt hp cc khi nh ni c phn tch a ra cc i tng c lm sch.Xc nh tnh cht i tng: Xc nh hnh bao, din tch, v tr, Lc x l im nh ni

Bi ton 2Phn loi i tngBa phng php phn loi i tngPhn loi da trn hnh dng (shape)Phn loi da trn s chuyn ng (motion)Phn loi da trn s kt hp hnh dng v chuyn ngPhn loi da trn hnh dng (shape)

Phn loi da trn hnh dng (shape)

Phn loi da trn s chuyn ng (motion)

Phn loi da trn s kt hp hnh dng v chuyn ng

Bi ton 3Theo di i tngTheo vt i tng

Cc phng php s dng theo di i tngTheo vt da vo m hnh: H thng theo vt da vo m hnh 2D-3D. chnh xc cao, s lng i tng theo di t. Theo vt i tng da vo min: Nhn dng nhng min lin kt vi nhau trong nh, khi m c lin kt vi mc tiu c theo di. Theo vt i tng da vo ng bao ng (Active Contour): ng vin bao i tng c theo di, v lin tc cp nht t ng. Hn ch chnh ca cch tip cn ny l x l th no vi trng hp nhp nhng.Theo vt i tng da vo c trng: Cc c trng nh tm, mu sc ca i tng. Cch tip cn ny s dng m hnh Kalman.Chnh xc ha i tng, x l nhp nhng

Phng php D on chuyn ng

Phn 3. Tnh hnh nghin cu trong v ngoi ncTnh hnh nghin cu trong v ngoi ncGii thiu khi qut cc nghin cu Gii thiu mt s kt qu nghin cu

Gii thiu khi qut cc nghin cu [1] Gii thiu tng quan v 03 bi ton hp thnh trong bi ton pht hin, phn loi v theo di i tng chuyn ng. Trong gii thiu phng php pht hin: gim tr nn, cc phng php thng k, phng php chnh lch thi gian; phng php phn loi i tng: phn loi da trn hnh dng, phn loi da trn chuyn ng; phng php theo di i tng chuyn ng: Kalman filter, SSD, MS.[2] Lun vn tin s ca L Quc Ngc v xy dng tm kim nh da trn ni dung, trong xy dng mt ph h tri thc th gic cho nh nh: Mu (sc mu, thun khit, sng)Dng (dng i tng, kch thc i tng)Dng i tng (dng ton cc, dng cc b)Dng ton cc (trn, elip, vung, ch nht, cong,...)

Gii thiu khi qut cc nghin cu [3] Gii thiu s khi qut v h thng nhn dng Nguyn ng Bnh. i hc Khoa hc T nhin Hu. 2012. (slide 67)[4] Tng quan v phn on nh.nh gi khi qut v 7 phng php s dng trong phn on nh (trang 47), gii thiu chi tit v phng php phn on da pht hin bin i tng nh.[6] L thuyt nhn dng.Gii thiu khi qut v l thuyt nhn dng i tng nh, trong nhn dng nh c phn loi l: nhn dng da trn phn hoch khng gian, nhn dng da trn cu trc, nhn dng da trn mng n ron. [8] Tng hp v gii thiu 15 cng trnh nghin cu trn th gii v phng php v s cng ngh nhn dng xe t trong video giao thng.[9] Gii thiu khung khai ph d liu video bao gm 5 tng[10] Gii thiu phng php tnh ton di th gic ca t qua tiu c, cao t my quay, gc quay i tng, tnh ton xc nh loi xe di hay ngn, cng nh x l cc trng hp nhp nhng trong nh gia cc t dnh nhau theo chiu dc v chiu ngang.[11, 12, 14, 17] Cng trnh v sch chuyn kho v nhn dng v x l nh.[13] Tng hp cc cng trnh nghin cu c cng b trong hi ngh v khm ph tri thc v khai ph d liu, nm 2002 ti n .[15, 16] Gii thiu kt qu minh ha cc thut ton x l nh trn nn Matlab.[18] Gii thiu vic xy dng mt h thng v The developed system is a multi-view tracking system based on the planar homography.Mt s kt qu nghin cu trn th giiH thng gim st giao thng t ng da trn th gic nhn dng v theo di t.Tch hp pht hin, theo di v nhn dng phn loi xe da trn video hng ngoiThit k h thng t ng nhn dng loi xe trong thi gian thc v ng dngH thng pht hin v phn loi xe nhm thu thp d liu cc phng tin trong thi gin thc da trn video quay bi camera khng hiu chnh

Cng trnh 1H thng gim st giao thng t ng nhn dng v theo di tda trn th gic.Automatic Traffic Surveillance System for Vision-Based Vehicle Recognition and Tracking.Chung-cheng chiu, Min-yu ku and Chun-yi wang, Department of Electrical and Electronic Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan, 335 Taiwan

S khi h thng

Cng trnh 2Tch hp pht hin, theo di v nhn dng phn loi xe da trn video hng ngoiIntegrated Detection Tracking and Recognition for IR Video-based Vehicle ClassificationXue Mei, University of Maryland, College Park, MD 20742, xuemei@cfar.umd.eduShaohua Kevin Zhou, Siemens Corporate Research, Princeton, NJ 08540, kzhou@scr.siemens.comHao Wu, Fatih Porikli, Mitsubishi Electric Research Labs, Cambridge, MA 02139, fatih@merl.com

S khi h thng

Cng trnh 3H thng t ng nhn dng loi xe trong thi gian thc v ng dngReal Time and Automatic Vehicle Type Recognition System Design and Its ApplicationWei Zhan, College of Computer Science Yangtze University Jingzhou, Hubei, China, Zhanwei814@gmail.comJunkai Yang International School Beijing University of Posts and Telecommunications, Beijing, China, yangjunkai91@gmail.com

S khi h thng

S khi h thng

Cng trnh 4H thng pht hin v phn loi xe nhm thu thp d liu cc phng tin trong thi gin thc da trn video quay bi camera khng hiu chnh.A Video-based Vehicle Detection and Classification System for Real-time Traffic Data Collection Using Uncalibrated Video Cameras Guohui Zhang (Corresponding Author), Research Assistant, Box 352700, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195-2700, E-mail: zhanggh@u.washington.eduRyan P. Avery, Research Assistant, Box 352700, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195-2700, E-mail: rpavery@u.washington.eduYinhai Wang, Ph.D. Assistant Professor, Box 352700, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195-2700, E-mail: yinhai@u.washington.edu

S khi h thng

Phn 4.Mt s phng php, thut ton s dng

1. Phng php tr nn (Background Subtraction)Hnh nh minh ha thut ton tr nn

1. Phng php tr nn (tip)S khi phng php tr nn

1. Phng php tr nn (tip)Mt im nh It(x,y) trong mt khung hnh mi v Bt(x,y) l im nh trn nh nn u c ta (x, y). im nh I c coi l im nh ni nu:

Trong l mt ngng c nh ngha t trc.nh nn B c cp nht cng thc sau:

Trong l im nh ni ti thi im t, l im nh nn ti thi im t, l tham s c nh ngha trc.

1. Phng php tr nn (tng thch) cng ca im nh ti v tr x gi tr cng ca nh nn biu din mt ngng c c lng thuc [0.0, 1.0] s im nh khc nhau

2. Pht hin bng i tngGi s:Ix biu din mu ca im nh khung hnh ti v tr x, Bxbiu din mu RGB ca im nh nn tng ng. l vector c gc l 0(0,0,0) trong h ta mu RGB l vector tng ng cho im nh l mt ngng xc nh trc

Nu:Th im nh Ix l bng ca i tng

3. Xc nh di th gic qua nhM hnh: R: Chiu di pixel trong nh phngDh1: Chiu di th gic trn ng F: ng tm ca camera R2 v R1 l cc chiu di pixel trong nh phng Rp: l kch thc im nh ca camera. H l cao ca camera, F: l tiu im ca ng knh l gc ca camera vi mt ng.

3. Xc nh di th gic qua nh

3. Xc nh di th gic qua nh

4. Pht hin binng bin l tng l s thay i gi tr cp xm ti mt v tr xc nh. V tr ca ng bin chnh l v tr thay i cp xm.

ng bin bc thang xut hin khi s thay i cp xm tri rng qua nhiu im nh. V tr ca ng bin c xem nh v tr chnh gia ca ng ni gia cp xm thp v cp xm cao. 4. Pht hin binK thut gradient dng ton t gradient, ly o hm theo mt hng;K thut la bn dng ton t la bn, ly o hm theo tm hng: Bc, Nam, ng, Ty, v ng Bc, Ty Bc, ng Nam, Ty Nam.

dx l khong cch gia cc im theo hng x, dy l khong cch gia cc im theo hng y. Thng thng ta s dng dx = dy = 1.4. Pht hin bina) K thut Gradient

Ton t Robert

Ton t Sobel

Ton t Prewitt

ng hng

4. Pht hin binb) Ton t la bn o gradient theo 8 hng. gk l gradient la bn theo hng qk = p/2+2kp, vi k = 0, 1, , 7. Ton t Kirsh. S dng mt n 3x3, mt n Hk ng vi hng qk vi k = 0, 1, 2,..., 7. Mt n H0 cho hng q0 = 00

7 mt n khc nhau t H1 n H7 cho 7 hng cn li: 450, 900, 1350, 1800, 2250, 2700, 3150.

4. Pht hin binc)Ton t Laplace nh ngha ton t Laplace

Ba mt n thng dng:

Phn 5Kt lunKt lun4.1. Cc vn trnh by4.2. Nhng vn lun n tp trung nghin cu, gii quyt4.2.1. La chn m hnh v thc nghim4.2.2. Phn tch, ci tin phng php, thut tonMt s vn cn nghin cu pht trinPhn tch, nh gi v la chn thut ton tr nn.Tch hp phi kt hp cc c trng hoc b sung c trng trong bi ton pht hin i tng p dng trong bi ton xc nh mt giao thng trong h thng gim st giao thng thng minh.X l cc trng hp nhp nhng.D kin cu trc lun nLI CAM OANLI CM NMC LCDANH MC CC K HIU, CH VIT TTDANH MC CC BNGDANH MC CC TH, HNH VM UCHNG 1. GII THIU TNG QUANCHNG 2. MT S PHNG PHP, THUT TON P DNGCHNG 3. XY DNG, PHT TRIN PHNG PHP MICHNG 4. THC NGHIMKT LUNTI LIU THAM KHO

D kin cu trc lun nM U1. TNH CP THIT CA TI2. MC TIU CA TI3. I TNG V PHM VI NGHIN CU4. PHNG PHP NGHIN CU5. NGHA L LUN V THC TIN CA TID kin cu trc lun nCHNG 1. GII THIU TNG QUAN1.1. T BI TON1.2. GII THIU KT QU MT S CNG TRNH NGHIN CUD kin cu trc lun nCHNG 2. MT S PHNG PHP, THUT TON P DNG2.1. GIM TR NN2.2. PHT HIN BIN2.3. PHT HIN BNG I TNG2.4. TNH TON DI TH GIC2.5. XC NH TRNG TM I TNG2.6. SO KHP MUD kin cu trc lun nCHNG 3. XY DNG, PHT TRIN PHNG PHP MI3.1. PHN LOI XE T V I TNG CHUYN NG KHC DA TRN S KT HP BIN V SO KHP MU3.2. PHN TCH I TNG DA TRN S KT HP DI TH GIC V TRNG TM I TNG3.3. C LNG S LNG CHUYN NG TRONG M NG DA TRN BIN V SO KHP MU3.1. PHN LOI XE T V I TNG CHUYN NG KHC DA TRN S KT HP BIN V SO KHP MU

3.3. C LNG S LNG CHUYN NG TRONG M NG DA TRN BIN V SO KHP MU

3.2. PHN TCH I TNG DA TRN S KT HP DI TH GIC V THUC TNH I TNG

D kin cu trc lun nCHNG 4. THC NGHIM4.1. KHO ST MT S KHUNG LM VIC THC HIN4.2. XUT KHUNG LM VIC MI4.3. KT QU THC NGHIM

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Ti liu tham kho40. A new approach to linear filtering and prediction problems. R. E. Kalman, Transactions of the ASME. Journal of Basic Engineering, Vol. 82, Series D, 196041. Robust real-time periodic motion detection, analysisandapplications. R. Cutler and L.S. Davis. In IEEE Transactions on Pattern Analysis and MachineIntelligence, volume 8, pages 781796, 2000.42. Image Based Measurement Systems: Object Recognition and Parameter Estimation. F. Heijden. Wiley, January 1996.43.Local application of optic flow to analyse rigid versus non-rigidmotion.A. J. Lipton. Technical Report CMU-RI-TR-99-13, Robotics Institute, CarnegieMellon University, Pittsburgh, PA, December 1999.Ti liu tham kho44.Moving target classification and tracking from real-time video. A. J. Lipton, H. Fujiyoshi, and R.S. Patil. In Proc. of Workshop Applications of ComputerVision, pages 129136, 1998.45.Classifying moving objects as rigid or non-rigid. L. Wixson and A. Selinger.In Proc. of DARPA Image Understanding Workshop, pages 341358, 199846.A system for video surveillance and monitoring: VSAM final report. R. T. Collins. Technical report CMU-RI-TR-00-12, Robotics Institute, CarnegieMellon University, May 2000.