Open AccessGait Recognition of Amur Tiger Based on Deep Learning
Author(s) -
Lili Zhou,
Tongjun Liu,
Du Yinfu,
Jinyu Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1966/1/012004
Subject(s) - tiger , gait , movement (music) , artificial intelligence , premise , computer vision , computer science , geography , physical medicine and rehabilitation , computer security , medicine , philosophy , linguistics , aesthetics
The gait of Amur tiger was studied through video images, and a more accurate individual recognition system of Wild Amur tiger was given on the premise of supplementing pattern recognition technology. Through further research on the common gait of Amur tiger, the basic information database was established to realize the physiological state research of Amur tiger. The characteristic structure and movement standard model of Amur tiger were constructed to complete the simulation and reconstruction of Amur tiger’s routine movement. Through the simulation corridor of tiger movement trajectory, the ecological protection area can be divided effectively.