Visual tracking with histograms and articulating blocks

S. M. Shahed Nejhum; Jeffrey Ho; Ming Hsuan Yang

doi:10.1109/CVPR.2008.4587575

Visual tracking with histograms and articulating blocks

S. M. Shahed Nejhum, Jeffrey Ho, Ming Hsuan Yang

College of Computing

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

103 Citations (Scopus)

Abstract

We propose an algorithm for accurate tracking of (articulated) objects using online update of appearance and shape. The challenge here is to model foreground appearance with histograms in a way that is both efficient and accurate. In this algorithm, the constantly changing foreground shape is modeled as a small number of rectangular blocks, whose positions within the tracking window are adaptively determined. Under the general assumption of stationary foreground appearance, we show that robust object tracking is possible by adaptively adjusting the locations of these blocks. Implemented in MATLAB without substantial optimization, our tracker runs already at 3.7 frames per second on a 3GHz machine. Experimental results have demonstrated that the algorithm is able to efficiently track articulated objects undergoing large variation in appearance and shape.

Original language	English
Title of host publication	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
DOIs	https://doi.org/10.1109/CVPR.2008.4587575
Publication status	Published - 2008
Event	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR - Anchorage, AK, United States Duration: 2008 Jun 23 → 2008 Jun 28

Publication series

Name	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Other

Other	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Country/Territory	United States
City	Anchorage, AK
Period	08/6/23 → 08/6/28

Bibliographical note

Funding Information:
M.-H. Yang is supported in part by a UC Merced faculty start-up fund and a gift from Google.

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Control and Systems Engineering

Access to Document

10.1109/CVPR.2008.4587575

Cite this

@inproceedings{c1d9c127ad284e21946152123ca4d864,

title = "Visual tracking with histograms and articulating blocks",

abstract = "We propose an algorithm for accurate tracking of (articulated) objects using online update of appearance and shape. The challenge here is to model foreground appearance with histograms in a way that is both efficient and accurate. In this algorithm, the constantly changing foreground shape is modeled as a small number of rectangular blocks, whose positions within the tracking window are adaptively determined. Under the general assumption of stationary foreground appearance, we show that robust object tracking is possible by adaptively adjusting the locations of these blocks. Implemented in MATLAB without substantial optimization, our tracker runs already at 3.7 frames per second on a 3GHz machine. Experimental results have demonstrated that the algorithm is able to efficiently track articulated objects undergoing large variation in appearance and shape.",

author = "{Shahed Nejhum}, {S. M.} and Jeffrey Ho and Yang, {Ming Hsuan}",

note = "Funding Information: M.-H. Yang is supported in part by a UC Merced faculty start-up fund and a gift from Google. ; 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR ; Conference date: 23-06-2008 Through 28-06-2008",

year = "2008",

doi = "10.1109/CVPR.2008.4587575",

language = "English",

isbn = "9781424422432",

series = "26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR",

booktitle = "26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR",

}

Shahed Nejhum, SM, Ho, J & Yang, MH 2008, Visual tracking with histograms and articulating blocks. in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR., 4587575, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Anchorage, AK, United States, 08/6/23. https://doi.org/10.1109/CVPR.2008.4587575

TY - GEN

T1 - Visual tracking with histograms and articulating blocks

AU - Shahed Nejhum, S. M.

AU - Ho, Jeffrey

AU - Yang, Ming Hsuan

N1 - Funding Information: M.-H. Yang is supported in part by a UC Merced faculty start-up fund and a gift from Google.

PY - 2008

Y1 - 2008

N2 - We propose an algorithm for accurate tracking of (articulated) objects using online update of appearance and shape. The challenge here is to model foreground appearance with histograms in a way that is both efficient and accurate. In this algorithm, the constantly changing foreground shape is modeled as a small number of rectangular blocks, whose positions within the tracking window are adaptively determined. Under the general assumption of stationary foreground appearance, we show that robust object tracking is possible by adaptively adjusting the locations of these blocks. Implemented in MATLAB without substantial optimization, our tracker runs already at 3.7 frames per second on a 3GHz machine. Experimental results have demonstrated that the algorithm is able to efficiently track articulated objects undergoing large variation in appearance and shape.

AB - We propose an algorithm for accurate tracking of (articulated) objects using online update of appearance and shape. The challenge here is to model foreground appearance with histograms in a way that is both efficient and accurate. In this algorithm, the constantly changing foreground shape is modeled as a small number of rectangular blocks, whose positions within the tracking window are adaptively determined. Under the general assumption of stationary foreground appearance, we show that robust object tracking is possible by adaptively adjusting the locations of these blocks. Implemented in MATLAB without substantial optimization, our tracker runs already at 3.7 frames per second on a 3GHz machine. Experimental results have demonstrated that the algorithm is able to efficiently track articulated objects undergoing large variation in appearance and shape.

UR - http://www.scopus.com/inward/record.url?scp=51949099485&partnerID=8YFLogxK

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U2 - 10.1109/CVPR.2008.4587575

DO - 10.1109/CVPR.2008.4587575

M3 - Conference contribution

AN - SCOPUS:51949099485

SN - 9781424422432

T3 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

BT - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

T2 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Y2 - 23 June 2008 through 28 June 2008

ER -

Visual tracking with histograms and articulating blocks

Abstract

Publication series

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Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

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Cite this