Gait recognition system to identify walking subject
AssigneeKing Fahd University of Petroleum and Minerals
InventorsAmer Ghazi Abdullah Binsaadoon, El-Sayed M. El-Alfy
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Abstract
Described is a novel method for feature extraction for automatic gait recognition. This method uses Multi-kernel Fuzzy-based Local Gabor Binary Pattern. From a captured gait video sequence, the gait period is determined then a gait energy image is constructed to represent the spatial-temporal variations during one motion cycle of the gait sequence. Then, each gait sequence is represented with a feature vector. The computation of this vector is conducted by first applying the 2D Gabor filter bank then encoding the variations in the Gabor magnitude using a multi-kernel fuzzy local binary pattern operator. Finally, gait classification is performed using a support vector machine.
Claims4
A gait recognition system comprising:
- a computer having one or more processors, and
- a video imaging system configured to capture a video sequence of a walking subject;
- wherein the one or more processors executing a program to perform steps comprising:
- determining a set of feature vectors from the video sequence of the walking subject;
- training the classification model with the set of feature vectors;
- and
- classifying a new video sequence in order to recognize the walking subject,
- wherein the determining the set of feature vectors comprises:
- inputting to the computer system a video sequence of the walking subject;
- determining an average image of images of the video sequence for a cycle;
- filtering the averaged image to obtain N filtered responses, N is a natural number greater than one;
- determining the magnitudes of the filtered responses for a center pixel pc and a selected plurality of neighbor pixels having a radius r;
- for each filtered response, determining for each of K different radiuses from the center pixel pc a plurality of fuzzy-based local patterns based on the magnitudes of the filtered responses, including applying a kernel fuzzy local binary pattern operator that sums magnitude differences of the filtered response for selected pixels at a respective same radius r from the center pixel pc, to generate the plurality of fuzzy-based local patterns for each of the respective K different radiuses, K is a natural number greater than one;
- for each filtered response, summing the fuzzy-based local patterns for each of the respective kernel fuzzy local binary pattern operators to form a histogram for a respective filtered response;
- forming feature vectors based on the histograms of the N filtered responses.
Dependencies are inferred from the claim text.