Open AccessAthlete Gait Feature Recognition Method Based on Multisource Sensing Information
Author(s) -
Xu Li,
Chunlei Xue,
Xiaobo Gu
Publication year - 2022
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2022/2857465
Subject(s) - gait , artificial intelligence , feature (linguistics) , computer science , computer vision , pattern recognition (psychology) , feature extraction , frame (networking) , gait analysis , physical medicine and rehabilitation , medicine , telecommunications , philosophy , linguistics
Aiming at the problem of low accuracy of two-dimensional gait recognition at present, a gait feature recognition method based on multisource sensing information is proposed. The multisource sensing information is combined to collect the athlete’s gait characteristics, collect the single frame gait image sequence of the human lower limbs during the movement, and extract the human body’s three-dimensional feature data during human walking by using the body structure and multisource sensing information, so as to realize the separation of the athlete’s gait image background. Finally, it is confirmed by experiments that the recognition rate of athlete gait feature recognition method based on multisource sensing information is significantly improved.
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