无线电电子学、计算机技术 |
|
|
|
|
基于核密度估计的遮挡人体跟踪 |
王选贺, 刘济林 |
浙江大学 信息与通信工程研究所, 浙江省综合信息网技术重点实验室,浙江 杭州 310027 |
|
Tracking human under occlusion based on kernel density estimation |
WANG Xuan-he, LIU Ji-lin |
Institute of Information and Communication Engineering, Zhejiang Provincial Key Laboratory of
Information Network Technology, Zhejiang University, Hangzhou 310027, China |
[1] KANG J, COHEN I, MEDIONI G. Tracking people in crowded scenes across multiple cameras[C]∥Proceedings of Asian Conference on Computer Vision. [S.l.]:[s.n.], 2004:157-168.
[2] MITTAL A,DAVIS L. M2tracker: a multiview approach to segmenting and tracking people in a cluttered scene[J]. International Journal of Computer Vision, 2003,51(3):189-203.
[3] OTSUKA K,MUKAWA N. Multiview occlusion analysis for tracking densely populated objects based on 2d visual angles[C]∥Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.[S.l.]:[s.n.],2004:1-90.
[4] BlACK J,EllIS T,ROSIN P. Multiview image surveillance and tracking[C]∥Proceedings of Workshop on Motion and Video Computing, 2002: 169-178.
[5] KHAN S,SHAH M. Tracking groups of people in presence of occlusion[C] ∥The 4th PacificRim Symposium on Image and Video Technology.[S.l.]:[s.n.],2000:438-446.
[6] SMITH K,GATICAPEREZ D,ODOBEZ J M. Using particles to track varying numbers of interacting people[C] ∥Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.San Diego:IEEE,2005:962-970.
[7] HAN M, XU W, TAO H,et al. An algorithm for multiple object trajectory tracking[C]∥ Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. [S.l.]:IEEE,2004: 864-871.
[8] ISARD M,MAC J C. Bramble: a bayesian multipleblob tracker[C] ∥Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. [S.l.]:IEEE,2001,2: 34-41.
[9] COMANICIU D,MEER P. Mean shift analysis and application[C]∥Proceedings of the 7th IEEE International Conference on Computer Vision.[S.l.]:IEEE, 1999:1197-1203.
[10] STAUFFER C,GRIMSON W E L. Adaptive Background Mixture Models for Realtime Tracking[C]∥Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Fort Collins. \
[S.l.\]:\
[s.n.\],1999:154-167.
[11] COMANICIU D, RAMESH V,MEER P.The variable bandwidth mean shift and datadriven scale selection[C]∥Proceedings of the 8th International Conference on Computer Vision. [S.l.]:[s.n.],2001:438-445.
[12] COMANICIU D, MEER P. Meanshift: a robust approach toward feature space analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(4):603-619.
[13] DAVID W S,SAIN S R. Multidimensional density estimation[J].Elsevier B V, 2004:24(5):229-260.
[14] DUONG T, HAZELTON M L. Crossvalidation bandwidth matrices for multivariate kernel density estimation[J]. Scandinavian Journal of Statistics, 2005,32:485-506.
[15] YANG C,DURAISWAMI R,GUMEROV N,et al. Improved fast gauss transform and efficient kernel density estimation[C] ∥Proceedings of IEEE International Conference on Computer Vision.[S.l.]:IEEE,2003: 464-471.
[16] COMANICIU D, RAMESH V, MEER P. Realtime tracking of nonrigid objects using mean shift[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.[S.l.]:IEEE,Hilton Head Island,2000:142-151. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|