Simplest Representation Yet for Gait Recognition: Averaged Silhouette
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Fast communication: Gait recognition based on dynamic region analysis
Signal Processing
Fast communication: Active energy image plus 2DLPP for gait recognition
Signal Processing
Self-calibrating view-invariant gait biometrics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Pattern Recognition Letters
Fusion of static and dynamic body biometrics for gait recognition
IEEE Transactions on Circuits and Systems for Video Technology
Random Subspace Method for Gait Recognition
ICMEW '12 Proceedings of the 2012 IEEE International Conference on Multimedia and Expo Workshops
Robust Clothing-Invariant Gait Recognition
IIH-MSP '12 Proceedings of the 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
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Gait recognition systems often suffer from the challenges when query gaits are under the coupled effects of unknown view angles and large intra-class variations (e.g., wearing a coat). In this paper, we deem it as a two-stage classification problem, namely, view detection and fixed-view gait recognition. First, we propose two simple yet effective feature types (i.e., global features and local features) for view detection. By using the detected view information, the corresponding gallery (i.e., enrolled gait) for the detected view can be adaptively selected to perform the fixed-view gait recognition. For fixed-view gait recognition, since the inter-class variations for training are normally small, whereas the query gait usually has large intra-class variations, random subspace method are adopted. We evaluate our approach on the largest multi-view gait database CASIA-B dataset. The avoidance of searching whole multi-view database as well as the competitive performance indicate that our proposed method is practical for gait recognition in real world surveillance scenarios.