TY - GEN
T1 - Symmetrical judgment and improvement of CoHOG feature descriptor for pedestrian detection
AU - Kataoka, Hirokatsu
AU - Aoki, Yoshimitsu
PY - 2011/12/1
Y1 - 2011/12/1
N2 - Pedestrian detection method is the highest priority for "active safety" which prevents traffic accidents before happens. In previous studies, edge orientation based feature descriptors are proposed. Recently, high standard detection algorithm, Co-occurrence Histograms of Oriented Gradients (CoHOG) is proposed. However, this method has miss detection in complicated situation and processing cost is high. We propose symmetrical judgment algorithm and an extended version of CoHOG for high speed and high accuracy pedestrian detection. The effectiveness of the proposed method was proved on pedestrian detection performance test.
AB - Pedestrian detection method is the highest priority for "active safety" which prevents traffic accidents before happens. In previous studies, edge orientation based feature descriptors are proposed. Recently, high standard detection algorithm, Co-occurrence Histograms of Oriented Gradients (CoHOG) is proposed. However, this method has miss detection in complicated situation and processing cost is high. We propose symmetrical judgment algorithm and an extended version of CoHOG for high speed and high accuracy pedestrian detection. The effectiveness of the proposed method was proved on pedestrian detection performance test.
UR - http://www.scopus.com/inward/record.url?scp=84872508470&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:84872508470
SN - 9784901122115
T3 - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
SP - 536
EP - 539
BT - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
T2 - 12th IAPR Conference on Machine Vision Applications, MVA 2011
Y2 - 13 June 2011 through 15 June 2011
ER -
