Multiple collaborative kernel tracking

Zhimin Fan; Ying Wu; Ming Yang

doi:10.1109/CVPR.2005.242

Multiple collaborative kernel tracking

Zhimin Fan^*, Ying Wu, Ming Yang

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

68 Scopus citations

Abstract

This paper presents a novel multiple collaborative kernel approach to visual tracking. This approach treats kernel-based tracking in a more general setting, i.e., a relaxation and constraints formulation, in which a complex motion is represented by a set of inter-correlated simpler motions. With this formulation, we present a rigorous analysis on a critical issue of kernel observability and obtain a criterion, based on which we propose a new method using collaborative kernels that has the theoretical guarantee of enhanced observability. This new method has been shown to be computationally efficient in both theory and practice, which can be readily applied to complex motions such as articulated motions.

Original language	English (US)
Title of host publication	Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Publisher	IEEE Computer Society
Pages	502-509
Number of pages	8
ISBN (Print)	0769523722, 9780769523729
DOIs	https://doi.org/10.1109/CVPR.2005.242
State	Published - 2005
Event	2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - San Diego, CA, United States Duration: Jun 20 2005 → Jun 25 2005

Publication series

Name	Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Volume	II

Other

Other	2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Country/Territory	United States
City	San Diego, CA
Period	6/20/05 → 6/25/05

ASJC Scopus subject areas

General Engineering

Access to Document

10.1109/CVPR.2005.242

Cite this

Fan, Z., Wu, Y., & Yang, M. (2005). Multiple collaborative kernel tracking. In Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 (pp. 502-509). Article 1467483 (Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005; Vol. II). IEEE Computer Society. https://doi.org/10.1109/CVPR.2005.242

@inproceedings{9cc8665e93ba46d7aca4e92dc9a36a6a,

title = "Multiple collaborative kernel tracking",

abstract = "This paper presents a novel multiple collaborative kernel approach to visual tracking. This approach treats kernel-based tracking in a more general setting, i.e., a relaxation and constraints formulation, in which a complex motion is represented by a set of inter-correlated simpler motions. With this formulation, we present a rigorous analysis on a critical issue of kernel observability and obtain a criterion, based on which we propose a new method using collaborative kernels that has the theoretical guarantee of enhanced observability. This new method has been shown to be computationally efficient in both theory and practice, which can be readily applied to complex motions such as articulated motions.",

author = "Zhimin Fan and Ying Wu and Ming Yang",

year = "2005",

doi = "10.1109/CVPR.2005.242",

language = "English (US)",

isbn = "0769523722",

series = "Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005",

publisher = "IEEE Computer Society",

pages = "502--509",

booktitle = "Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005",

address = "United States",

note = "2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 ; Conference date: 20-06-2005 Through 25-06-2005",

}

Fan, Z, Wu, Y & Yang, M 2005, Multiple collaborative kernel tracking. in Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005., 1467483, Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. II, IEEE Computer Society, pp. 502-509, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, San Diego, CA, United States, 6/20/05. https://doi.org/10.1109/CVPR.2005.242

Multiple collaborative kernel tracking. / Fan, Zhimin; Wu, Ying; Yang, Ming.
Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005. IEEE Computer Society, 2005. p. 502-509 1467483 (Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005; Vol. II).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Multiple collaborative kernel tracking

AU - Fan, Zhimin

AU - Wu, Ying

AU - Yang, Ming

PY - 2005

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N2 - This paper presents a novel multiple collaborative kernel approach to visual tracking. This approach treats kernel-based tracking in a more general setting, i.e., a relaxation and constraints formulation, in which a complex motion is represented by a set of inter-correlated simpler motions. With this formulation, we present a rigorous analysis on a critical issue of kernel observability and obtain a criterion, based on which we propose a new method using collaborative kernels that has the theoretical guarantee of enhanced observability. This new method has been shown to be computationally efficient in both theory and practice, which can be readily applied to complex motions such as articulated motions.

AB - This paper presents a novel multiple collaborative kernel approach to visual tracking. This approach treats kernel-based tracking in a more general setting, i.e., a relaxation and constraints formulation, in which a complex motion is represented by a set of inter-correlated simpler motions. With this formulation, we present a rigorous analysis on a critical issue of kernel observability and obtain a criterion, based on which we propose a new method using collaborative kernels that has the theoretical guarantee of enhanced observability. This new method has been shown to be computationally efficient in both theory and practice, which can be readily applied to complex motions such as articulated motions.

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DO - 10.1109/CVPR.2005.242

M3 - Conference contribution

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SN - 9780769523729

T3 - Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

SP - 502

EP - 509

BT - Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

PB - IEEE Computer Society

T2 - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

Y2 - 20 June 2005 through 25 June 2005

ER -

Multiple collaborative kernel tracking

Abstract

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ASJC Scopus subject areas

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