DocumentCode :
3022328
Title :
Advances in automatic gait recognition
Author :
Nixon, Mark S. ; Carter, John N.
Author_Institution :
Sch. of Electron. & Comput. Sci., Southampton Univ., UK
fYear :
2004
fDate :
17-19 May 2004
Firstpage :
139
Lastpage :
144
Abstract :
Automatic recognition by gait is subject to increasing interest and has the unique capability to recognize people at a distance when other biometrics are obscured. Its interest is reinforced by the longstanding computer vision interest in automated non-invasive analysis of human motion. Its recognition capability is supported by studies in other domains such as medicine (biomechanics), mathematics and psychology, which continue to suggest that gait is unique. Further, examples of recognition by gait can be found in literature, with early reference by Shakespeare concerning recognition by the way people walk. Current approaches confirm the early results that suggested gait could be used for identification, and now on much larger databases. This has been especially influenced by the human ID at a distance research program with its wide scenario of data and approaches. Gait has benefited from the developments in other biometrics and has led to new insight particularly in view of covariates. As such, gait is an interesting research area, with contributions not only to the field of biometrics but also to the stock of new techniques for the extraction and description of objects moving within image sequences.
Keywords :
biometrics (access control); computer vision; feature extraction; gait analysis; image sequences; automatic gait recognition; biometrics; computer vision; distance research program; image sequences; object extraction; recognition capability; Biomechanics; Biomedical imaging; Biometrics; Computer vision; Data mining; Databases; Humans; Mathematics; Motion analysis; Psychology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on
Print_ISBN :
0-7695-2122-3
Type :
conf
DOI :
10.1109/AFGR.2004.1301521
Filename :
1301521
Link To Document :
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