Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Application of Principal Component Analysis and Neural Network on the Information System Evaluation
PACCS '09 Proceedings of the 2009 Pacific-Asia Conference on Circuits, Communications and Systems
Improved Gait Recognition Performance Using Cycle Matching
WAINA '10 Proceedings of the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops
Low-resolution gait recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Automatic gait recognition based on statistical shape analysis
IEEE Transactions on Image Processing
Fusion of face and speech data for person identity verification
IEEE Transactions on Neural Networks
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Gait is a biometric identification technology, which can identify people from distance, without user cooperation. This paper proposes a simple and efficient automatic gait recognition method taking frontal view silhouette of walking person using principal component analysis. Here for each image, background subtraction method is applied to extract the moving silhouette. These silhouette images are used to extract features using principal component analysis algorithm. Here principal component analysis method is applied to reduce the dimensionality of feature vectors. These reduce features vector represent the most relevant information of walking person, which are able to distinguish one people from others. Our result shows that taking frontal view image for recognition, gives good results. In our work the recognition rate is 97.50%.