Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
IEEE Transactions on Pattern Analysis and Machine Intelligence
New Area Based Metrics for Gait Recognition
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Gait-Based Recognition of Humans Using Continuous HMMs
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Towards a View Invariant Gait Recognition Algorithm
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Outdoor recognition at a distance by fusing gait and face
Image and Vision Computing
Filterbank-based fingerprint matching
IEEE Transactions on Image Processing
Biometric Gait Recognition with Carrying and Clothing Variants
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
International Journal of Biometrics
Interacting with Computers
Genetic programming for multibiometrics
Expert Systems with Applications: An International Journal
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Human gait is a spatio-temporal phenomenon and typifies the motion characteristics of an individual. The gait of a person is easily recognisable when extracted from a side view of the person. Accordingly, gait-recognition algorithms work best when presented with images where the person walks parallel to the camera (i.e. the image plane). A set of stances or key frames that occur during the walk cycle of an individual is chosen. This paper presents a novel approach adopted in automatic gait recognition in which the silhouette extracted is represented using Shannon entropy and extracts the height of the subject and periodicity of the gait. To classify unknown gait, they need to match the nearest neighbour in the stored database of extracted gait features, and the proposed approach are tested on the data sets and is found to be quite satisfactory in natural walk conditions. In addition, the proposed decision fusion enables the performance improvement by integrating multiple ones with different confidence measures.