| 1 |
Collins R T Liu Y Leordeanu M Online selection of discriminative tracking featuresIEEE Transactions on Pattern Analysis and MachineIntelligence 2005 27(10)16311643.
doi:10.1109/TPAMI.2005.205
|
| 2 |
Han B Davis L Robust observations for objecttrackingIn: Proceedings of the 12th InternationalConference on Image ProcessingWashingtonIEEE Press 2005 2442445
|
| 3 |
Yang C Duraiswami R Davis L Efficient mean-shift tracking via a new similarity measureIn: Proceedings of IEEE Computer Society Conferenceon Computer Vision and Pattern RecognitionWashingtonIEEE Press 2005 1176183
|
| 4 |
Comaniciu D Ramesh V Meer P Real-time tracking of non-rigid objects using mean shiftIn: Proceedings of the 1st Conference on ComputerVision and Pattern RecognitionWashingtonIEEE Press 2000 2142149
|
| 5 |
Jepson A D Fleet D J EI-Maraghi T F Robust online appearance models for visual trackingIEEE Transactions on Pattern Analysis and MachineIntelligence 2003 25(10)12961311.
doi:10.1109/TPAMI.2003.1233903
|
| 6 |
Comaniciu D Ramesh V Meer P Kernel-based object trackingIEEE Transactions on Pattern Analysis and Machine Intelligence 2003 25(5)564577.
doi:10.1109/TPAMI.2003.1195991
|
| 7 |
Li P Francois C Image cues fusion for objecttracking based on particle filterIn: Francisco JBruce AArticulated Motion and Deformable Objects. Lecture Notes in ComputerScienceBerlinSpringer-Verlag 2004 317999107
|
| 8 |
Wang H Suter D Efficient visual tracking byprobabilistic fusion of multiple cuesIn: Proceedings of 18th International Conference on Pattern RecognitionWashingtonIEEEPress 2006 4892895
|
| 9 |
Triesch J Von der Malsburg C Democratic integration: self-organizedintegration of adaptive cuesNeural Computation 2001 13(9)20492074.
doi:10.1162/089976601750399308
|
| 10 |
Spengler M Schiele B Towards robust multi-cue integrationfor visual trackingMachine Vision and Applications 2003 14(1)5058.
doi:10.1007/s00138‐002‐0095‐9
|
| 11 |
Shen C Van den Hengel A Dick A Probabilistic multiple cue integration for particle filterbased trackingIn: Proceedings of the 7thDigital Image Computing: Techniques and ApplicationsSydneyThe Universityof Queensland 2003 399408
|
| 12 |
Pérez P Vermaak J Blake A Data fusion for tracking with particlesIn: Proceedings of the IEEE 2004 92(3)495513.
doi:10.1109/JPROC.2003.823147
|
| 13 |
Loy G Fletcher L Apostoloff N et al.An adaptive fusion architecture for target trackingIn: Proceedings of the Fifth IEEE International Conferenceon Automatic Face and Gesture RecognitionWashingtonIEEE Press 2002 261266
|
| 14 |
Wu Y Huang T S Robust visual tracking by integratingmultiple cues based on co-inference learningInternational Journal of Computer Vision 2004 58(1)5571.
doi:10.1023/B:VISI.0000016147.97880.cd
|
| 15 |
Gordon N Salmond D Smith A A novel approach to nonlinear/non-Gaussian Bayesian stateestimationIn: IEEE Proceedings-F 1993 140(2)107113
|
| 16 |
Nummiaro K Koller-Meier E Gool L V An adaptive color-based particle filterImage and Vision Computing 2003 21(1)99110.
doi:10.1016/S0262‐8856(02)00129‐4
|
| 17 |
Isard M Blake A Condensation–conditionaldensity propagation for visual trackingInternational Journal of Computer Vision 1998 29(1)528.
doi:10.1023/A:1008078328650
|
| 18 |
Bhattacharyya A Ona measure of divergence between two statistical populations definedby their probability distributionsBulletinof the Calcutta Mathematical Society 1943 3599110
|
| 19 |
Brasnett P Mihaylova L Bull D et al.Sequential Monte Carlo tracking by fusing multiplecues in video sequencesImage and VisionComputing 2007 25(8)12171227.
doi:10.1016/j.imavis.2006.07.017
|
| 20 |
Goubet E Katz J Porikli F Pedestrian tracking using thermal infrared imagingMitsubishi Electric Research Laboratories TechnicalReport TR126 2005
|
