The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-2/W4
https://doi.org/10.5194/isprs-archives-XLII-2-W4-207-2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-207-2017
10 May 2017
 | 10 May 2017

GAIT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORKS

A. Sokolova and A. Konushin

Keywords: Gait Recognition, Biometrics, Convolutional Neural Networks, Optical Flow

Abstract. In this work we investigate the problem of people recognition by their gait. For this task, we implement deep learning approach using the optical flow as the main source of motion information and combine neural feature extraction with the additional embedding of descriptors for representation improvement. In order to find the best heuristics, we compare several deep neural network architectures, learning and classification strategies. The experiments were made on two popular datasets for gait recognition, so we investigate their advantages and disadvantages and the transferability of considered methods.