TY - GEN
T1 - Pedestrian detection using hybrid statistical feature
AU - Wu, Qiang
AU - Du, Chunhua
AU - Yang, Jie
AU - He, Xiangjian
AU - Chen, Yan
PY - 2008
Y1 - 2008
N2 - 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 nonhuman objects data.
AB - 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 nonhuman objects data.
UR - http://www.scopus.com/inward/record.url?scp=58049123940&partnerID=8YFLogxK
U2 - 10.1109/MMSP.2008.4665056
DO - 10.1109/MMSP.2008.4665056
M3 - Conference contribution
AN - SCOPUS:58049123940
SN - 9781424422951
T3 - Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008
SP - 101
EP - 106
BT - Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008
T2 - 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008
Y2 - 8 October 2008 through 10 October 2008
ER -