[1] Lin Guoyu, Yang Biao, Zhang Weigong,. Human tracking in camera network with non-overlapping FOVs [J]. Journal of Southeast University (English Edition), 2012, 28 (2): 156-163. [doi:10.3969/j.issn.1003-7985.2012.02.005]

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

28

Issue:

2012 2

Page:

156-163

Research Field:

Computer Science and Engineering

Publishing date:

2012-06-30

Info

Title:

Human tracking in camera network with non-overlapping FOVs

Author(s):

Lin Guoyu;  Yang Biao;  Zhang Weigong

School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China

Keywords:

multiple camera tracking;  non-overlapping FOVs;  spatio-temporal information;  human appearance model;  incremental learning

PACS:

TP391

DOI:

10.3969/j.issn.1003-7985.2012.02.005

Abstract:

An adaptive human tracking method across spatially separated surveillance cameras with non-overlapping fields of views(FOVs)is proposed. The method relies on the two cues of the human appearance model and spatio-temporal information between cameras. For the human appearance model, an HSV color histogram is extracted from different human body parts(head, torso, and legs), then a weighted algorithm is used to compute the similarity distance of two people. Finally, a similarity sorting algorithm with two thresholds is exploited to find the correspondence. The spatio-temporal information is established in the learning phase and is updated incrementally according to the latest correspondence. The experimental results prove that the proposed human tracking method is effective without requiring camera calibration and it becomes more accurate over time as new observations are accumulated.

References:

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Memo

Memo:

Biography: Lin Guoyu(1979—), male, doctor, lecturer, Andrew_Lin@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.60972001), the Science and Technology Plan of Suzhou City(No.SG201076).
Citation: Lin Guoyu, Yang Biao, Zhang Weigong. Human tracking in camera network with non-overlapping FOVs[J].Journal of Southeast University(English Edition), 2012, 28(2):156-163.[doi:10.3969/j.issn.1003-7985.2012.02.005]

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