TY - GEN
T1 - Human action recognition in videos using motion impression image
AU - Liu, Si
AU - Liu, Jing
AU - Zhang, Tianzhu
AU - Lu, Hanqing
PY - 2009
Y1 - 2009
N2 - Human action recognition in surveillance has become a hot topic in computer vision. In this paper, we develope a new method to recognize human action using motion information in video. Video sequence is compressed along time axis into a Motion Impression Image (MII), which is combined with two types of impression images from different views. One is a Period Impression Image (PII) by exploring the characteristics of the motion frequency. The other is an Optical Flow Impression Image (OFII) obtained from the analysis of motion mode. The proposed MII is a compact and time-invariant representation. Furthermore, it is simple and efficient to implement. After quantizing the combined MIIs, we feed them into a spatial pyramid matching kernel (SPMK) based classifier to recognize various human actions. At last, experiments on a known benchmark dataset demonstrate the better performance of the proposed approach against the state-of-the-art algorithms.
AB - Human action recognition in surveillance has become a hot topic in computer vision. In this paper, we develope a new method to recognize human action using motion information in video. Video sequence is compressed along time axis into a Motion Impression Image (MII), which is combined with two types of impression images from different views. One is a Period Impression Image (PII) by exploring the characteristics of the motion frequency. The other is an Optical Flow Impression Image (OFII) obtained from the analysis of motion mode. The proposed MII is a compact and time-invariant representation. Furthermore, it is simple and efficient to implement. After quantizing the combined MIIs, we feed them into a spatial pyramid matching kernel (SPMK) based classifier to recognize various human actions. At last, experiments on a known benchmark dataset demonstrate the better performance of the proposed approach against the state-of-the-art algorithms.
KW - Action recognition
KW - Feature extraction
KW - Optical flow impression image
KW - Period impression image
UR - https://www.scopus.com/pages/publications/77951572321
U2 - 10.1145/1734605.1734647
DO - 10.1145/1734605.1734647
M3 - 会议稿件
AN - SCOPUS:77951572321
SN - 9781605588407
T3 - 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009
SP - 174
EP - 178
BT - 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009
T2 - 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009
Y2 - 23 November 2009 through 25 November 2009
ER -