NDLI: Individual recognition from periodic activity using hidden Markov models

Content Provider	IEEE Xplore Digital Library
Author	Qiang He Debrunner, C.
Copyright Year	2000
Description	Author affiliation: Div. of Eng., Colorado Sch. of Mines, Golden, CO, USA (Qiang He)
Abstract	We present a method for recognizing individuals from their walking and running gait. The method is based on Hu moments of the motion segmentation in each frame. Periodicity is detected in such a sequence of feature vectors by minimizing the sum of squared differences, and the individual is recognized from the feature vector sequence using hidden Markov models. Comparisons are made to earlier periodicity detection approaches and to earlier individual recognition approaches. Experiments show the successful recognition of individuals (and their gait) in frontoparallel sequences.
Starting Page	47
Ending Page	52
File Size	522686
Page Count	6
File Format	PDF
ISBN	0769509398
DOI	10.1109/HUMO.2000.897370
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-12-08
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Image segmentation Computer vision Image recognition Motion segmentation Hidden Markov models Humans Pattern recognition Image sequences Helium
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Individual recognition from periodic activity using hidden Markov models