DocumentCode
3266930
Title
Pedestrian detection using hybrid statistical feature
Author
Wu, Qiang ; Du, Chunhua ; Yang, Jie ; He, Xiangjian ; Chen, Yan
Author_Institution
Sch. of Comput. & Commun., Univ. of Technol., Sydney, NSW
fYear
2008
fDate
8-10 Oct. 2008
Firstpage
101
Lastpage
106
Abstract
A novel approach for walking people detection is proposed in this paper, which is inspired by the idea of gait energy image (GEI). Unlike most of common human detection methods where usually a trained detector scans a single image and then generates a detection result, the proposed method detects people on a sequence of silhouettes which contain both appearance characteristics and motion characteristics. Thus, our method is more robust. Encouraging experimental results are obtained based on CASIA gait database and the additional non-human objects data.
Keywords
feature extraction; image sequences; object detection; statistical analysis; CASIA gait database; gait energy image; human detection methods; hybrid statistical feature; nonhuman objects data; pedestrian detection; walking people detection; Assembly; Australia; Detectors; Humans; Layout; Legged locomotion; Motion detection; Spatial databases; Support vector machines; Surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Signal Processing, 2008 IEEE 10th Workshop on
Conference_Location
Cairns, Qld
Print_ISBN
978-1-4244-2294-4
Electronic_ISBN
978-1-4244-2295-1
Type
conf
DOI
10.1109/MMSP.2008.4665056
Filename
4665056
Link To Document