TY - GEN
T1 - HMM-based segmentation and recognition of human activities from video sequences
AU - Niu, Feng
AU - Abdel-Mottaleb, Mohamed
PY - 2005/12/1
Y1 - 2005/12/1
N2 - Recognizing human activities from image sequences is an active area of research in computer vision. Most of the previous work on activity recognition focuses on recognition from video clips that show only single activities. There are few published algorithms for segmenting and recognizing complex activities that are composed of more than one single activity. In this paper, we present a novel HMM-based approach that uses threshold and voting to automatically and effectively segment and recognize complex activities. Experiments on a database of video clips of different activities show that our method is effective.
AB - Recognizing human activities from image sequences is an active area of research in computer vision. Most of the previous work on activity recognition focuses on recognition from video clips that show only single activities. There are few published algorithms for segmenting and recognizing complex activities that are composed of more than one single activity. In this paper, we present a novel HMM-based approach that uses threshold and voting to automatically and effectively segment and recognize complex activities. Experiments on a database of video clips of different activities show that our method is effective.
UR - http://www.scopus.com/inward/record.url?scp=33750537020&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750537020&partnerID=8YFLogxK
U2 - 10.1109/ICME.2005.1521545
DO - 10.1109/ICME.2005.1521545
M3 - Conference contribution
AN - SCOPUS:33750537020
SN - 0780393325
SN - 9780780393325
T3 - IEEE International Conference on Multimedia and Expo, ICME 2005
SP - 804
EP - 807
BT - IEEE International Conference on Multimedia and Expo, ICME 2005
T2 - IEEE International Conference on Multimedia and Expo, ICME 2005
Y2 - 6 July 2005 through 8 July 2005
ER -