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Multi-Pedestrian detection and tracking using unified multi-channel features

Title
Multi-Pedestrian detection and tracking using unified multi-channel features
Authors
Lim, Young ChulKang, Min Sung
DGIST Authors
Lim, Young Chul
Issue Date
2017-08-29
Citation
14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
Type
Conference
ISBN
9781538629390
ISSN
0000-0000
Abstract
This paper presents an online multiple pedestrian detection and tracking method using unified multi-channel features. The proposed method efficiently utilizes the multi-channel features by sharing them in each module: pedestrian detection, visual tracking, and data association. The multi-channel features are originally generated from the pedestrian detection module, and they represent sufficiently rich feature information. In the pedestrian detector, feature vectors for the pedestrian classifier are constructed from the unified multi-channel features, and the visual tracker localizes the target pedestrian on the multi-channel feature maps. An appearance model for data association is also established from the unified multi-channel features. Experimental results show that our method outperforms the state-of-the-art method in both accuracy and speed. © 2017 IEEE.
URI
http://hdl.handle.net/20.500.11750/5782
DOI
10.1109/AVSS.2017.8078506
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
Files:
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Collection:
Convergence Research Center for Future Automotive Technology2. Conference Papers


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