The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gait Sequence Analysis Using Frieze Patterns
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Stride and Cadence as a Biometric in Automatic Person Identification and Verification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Silhouette-Based Human Identification from Body Shape and Gait
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Baseline Results for the Challenge Problem of Human ID Using Gait Analysis
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Gait Analysis for Recognition and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gait Verification Using Probabilistic Methods
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Gait recognition using image self-similarity
EURASIP Journal on Applied Signal Processing
What image information is important in silhouette-based gait recognition?
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A novel approach on silhouette based human motion analysis for gait recognition
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Identification of humans using gait
IEEE Transactions on Image Processing
A new attempt to silhouette-based gait recognition for human identification
AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
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Recognition of a person from gait is a biometric of increasing interest. This paper presents a new approach on silhouette representation to extract gait patterns for human recognition. Silhouette shape of a motion object is first represented by four 1-D signals which are the basic image features called the distance vectors. The distance vectors are differences between the bounding box and silhouette. Second, eigenspace transformation based on Principal Component Analysis is applied to time-varying distance vectors and the statistical distance based supervised pattern classification is then performed in the lower-dimensional eigenspace for recognition. A fusion task is finally executed to produce final decision. Experimental results on three databases show that the proposed method is an effective and efficient gait representation for human identification, and the proposed approach achieves highly competitive performance with respect to the published gait recognition approaches.