Depth-Based Real-Time Gait Recognition (CROSBI ID 280616)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Ramakić, Adnan ; Sušanj, Diego ; Lenac, Kristijan ; Bundalo, Zlatko
engleski
Depth-Based Real-Time Gait Recognition
Each person describes unique patterns during gait cycles and this information can be extracted from live video stream and used for subject identification. In recent years, there has been a profusion of sensors that in addition to RGB video images also provide depth data in real- time. In this paper, a method to enhance the appearance-based gait recognition method by also integrating features extracted from depth data is proposed. Two approaches are proposed that integrate simple depth features in a way suitable for real-time processing. Unlike previously presented works which usually use a short range sensors like Microsoft Kinect, here, a long-range stereo camera in outdoor environment is used. The experimental results for the proposed approaches show that recognition rates are improved when compared to existing popular gait recognition methods.
Gait recognition ; depth data ; people identification ; long-range stereo camera ; GEI ; people height
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Podaci o izdanju
29 (16)
2020.
2050266
20
objavljeno
0218-1266
1793-6454
10.1142/s0218126620502667