Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
International Journal of Computer Vision
Fundamentals of speech recognition
Fundamentals of speech recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generative modeling for continuous non-linearly embedded visual inference
ICML '04 Proceedings of the twenty-first international conference on Machine learning
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Object Tracking Using Multiple Features
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Interactive Graph Cut Based Segmentation with Shape Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Bi-Layer Segmentation of Binocular Stereo Video
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Online Selection of Discriminative Tracking Features
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
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bilayer Segmentation of Live Video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
3D People Tracking with Gaussian Process Dynamical Models
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Progressive Refinement of Raster Images
IEEE Transactions on Computers
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Three-dimensional shape knowledge for joint image segmentation and pose estimation
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Gait recognition using a view transformation model in the frequency domain
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Monocular tracking of 3d human motion with a coordinated mixture of factor analyzers
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
POSECUT: simultaneous segmentation and 3D pose estimation of humans using dynamic graph-cuts
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Automatic gait recognition based on statistical shape analysis
IEEE Transactions on Image Processing
Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking
IEEE Transactions on Image Processing
Surveillance and human-computer interaction applications of self-growing models
Applied Soft Computing
People tracking and segmentation using efficient shape sequences matching
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
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We present an efficient people tracking and segmentation algorithm for gait recognition. Even though most existing gait recognition algorithms assume that people have been tracked and that silhouettes are available for gait classification, tracking and segmentation are very difficult especially for articulated objects such as human beings. We improve the performance of tracking and segmentation based on spatiotemporal shape constraints. First of all, we track people using an adaptive mean-shift tracker which produces initial results consisting of bounding boxes and foreground likelihood images. The initial results, generally speaking, are not accurate enough to be applied in gait recognition directly. We refine the results by matching with silhouette templates sequences in a batch mode to find the optimal silhouette-based gait paths corresponding to the input. Since the process is computationally expensive, we propose a novel efficient distance computation method to accelerate the spatiotemporal silhouette matching. The spatiotemporal shape priors are embedded into the Min-Cut algorithm to segment people out. Experiments on indoor and outdoor sequences demonstrate the effectiveness of the proposed approach.