Gait Sequence Analysis Using Frieze Patterns
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Automatic extraction and description of human gait models for recognition purposes
Computer Vision and Image Understanding
Silhouette-Based Human Identification from Body Shape and Gait
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
Matching Shape Sequences in Video with Applications in Human Movement Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Night Gait Recognition Based on Template Matching
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
3D tracking for gait characterization and recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Modelling the effect of view angle variation on appearance-based gait recognition
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Identification of humans using gait
IEEE Transactions on Image Processing
Automatic Gait Recognition Using Weighted Binary Pattern on Video
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
An efficient gait recognition with backpack removal
EURASIP Journal on Advances in Signal Processing
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Recent studies have shown that shape cues should dominate gait recognition. This motivates us to perform gait recognition through shape features in 2D human silhouettes. In this paper, we propose six simple projective features to describe human gait and compare eight kinds of projective features to figure out which projective directions are important to walker recognition. First, we normalize each original human silhouette into a square form. Inspired by the pure horizontal and vertical projections used in the frieze gait patterns, we explore the positive and negative diagonal projections with or without normalizing silhouette projections and obtain six new uniprojective features to characterize walking gait. Then this paper applies principal component analysis (PCA) to reduce the dimension of raw gait features. Finally, we recognize unknown gait sequences using the Mahalanobis-distance-based nearest neighbor rule. Experimental results show that the horizontal and diagonal projections have more discriminative clues for the side-view gait recognition and that the projective normalization generally can improve the robustness of projective features against the noise in human silhouettes.