Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Two- and three-dimensional patterns of the face
Two- and three-dimensional patterns of the face
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing planned multiperson action
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Digital Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tutorial on maximum likelihood estimation
Journal of Mathematical Psychology
Silhouette-Based Human Identification from Body Shape and Gait
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
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Identification Based on Gait (The Kluwer International Series on Biometrics)
Human Identification Based on Gait (The Kluwer International Series on Biometrics)
Discriminant Analysis with Tensor Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Gait Recognition by Gait Dynamics Normalization
IEEE Transactions on Pattern Analysis and Machine Intelligence
User Authentication based on Face Recognition with Support Vector Machines
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
A Bayesian Framework for Extracting Human Gait Using Strong Prior Knowledge
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Bayesian Networks
Gait recognition using linear time normalization
Pattern Recognition
A Component-based Framework for Face Detection and Identification
International Journal of Computer Vision
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
A Hierarchical Compositional Model for Face Representation and Sketching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic detection of abnormal gait
Image and Vision Computing
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Rate-invariant recognition of humans and their activities
IEEE Transactions on Image Processing
A Study of Parts-Based Object Class Detection Using Complete Graphs
International Journal of Computer Vision
Gait Components and Their Application to Gender Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Effect of silhouette quality on hard problems in gait recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Identification of humans using gait
IEEE Transactions on Image Processing
Human Gait Recognition With Matrix Representation
IEEE Transactions on Circuits and Systems for Video Technology
MPCA: Multilinear Principal Component Analysis of Tensor Objects
IEEE Transactions on Neural Networks
A survey of advances in biometric gait recognition
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Recognizing occluded faces by exploiting psychophysically inspired similarity maps
Pattern Recognition Letters
Combinational subsequence matching for human identification from general actions
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Gait recognition based on shape and motion analysis of silhouette contours
Computer Vision and Image Understanding
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Gait recognition algorithms often perform poorly because of low resolution video sequences, subjective human motion and challenging outdoor scenarios. Despite these challenges, gait recognition research is gaining momentum due to increasing demand and more possibilities for deployment by the surveillance industry. Therefore every research contribution which significantly improves this new biometric is a milestone. We propose a probabilistic sub-gait interpretation model to recognize gaits. A sub-gait is defined by us as part of the silhouette of a moving body. Binary silhouettes of gait video sequences form the basic input of our approach. A novel modular training scheme has been introduced in this research to efficiently learn subtle sub-gait characteristics from the gait domain. For a given gait sequence, we get useful information from the sub-gaits by identifying and exploiting intrinsic relationships using Bayesian networks. Finally, by incorporating efficient inference strategies, robust decisions are made for recognizing gaits. Our results show that the proposed model tackles well the uncertainties imposed by typical covariate factors and shows significant recognition performance.