Gait recognition using histograms of temporal gradients


Nair Mogan, Jashila and Lee, Chin Poo and Lim, Kian Ming (2020) Gait recognition using histograms of temporal gradients. Journal of Physics: Conference Series, 1502. 012051. ISSN 1742-6588

[img] Text
Restricted to Repository staff only

Download (824kB)


In this paper, we present a gait recognition method using convolutional features and histogramsof temporal gradients. The method comprises three stages, namely the convolutional stage, temporal gradient stage and classification stage. In the convolutional stage, the video frames are convolved with a set of pre-learned filters. This is followed by the temporal gradient stage. In this stage, the gradient of each convolved frame in time axis is calculated. Unlike histograms of oriented gradients that accumulate the gradients in the spatial domain, the proposed histogram of temporal gradients encodes the gradients in the spatial and temporal domain. The histogram of temporal gradients captures the gradient patterns ofevery pixel over the temporal axis throughout the video sequence. By doing so, the feature encodes both spatial and temporal information in the gait cycle. Finally, in the classification stage, a majority voting classification with Euclidean distance is performed for gait recognition. Experimental results show that the proposed method outperforms the state-of-the-art methods.

Item Type: Article
Uncontrolled Keywords: Biometric identification
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 16 Dec 2020 07:39
Last Modified: 16 Dec 2020 07:39


Downloads per month over past year

View ItemEdit (login required)