A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Active shape models—their training and application
Computer Vision and Image Understanding
Computer Vision for Interactive Computer Graphics
IEEE Computer Graphics and Applications
GREFIT: Visual Recognition of Hand Postures
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Real-Time 3-D Hand Posture Estimation Based on 2-D Appearance Retrieval Using Monocular Camera
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Real-Time Tracking of Multiple Persons
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Tracking Articulated Hand Motion with Eigen Dynamics Analysis
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Modelling and estimating the pose of a human arm
Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hand Gesture Extraction by Active Shape Models
DICTA '05 Proceedings of the Digital Image Computing on Techniques and Applications
One-Shot Learning of Object Categories
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Sharing Visual Features for Multiclass and Multiview Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-based hand pose estimation: A review
Computer Vision and Image Understanding
The Representation and Matching of Pictorial Structures
IEEE Transactions on Computers
Identifying elephant photos by multi-curve matching
Pattern Recognition
Human posture recognition for intelligent vehicles
Journal of Real-Time Image Processing
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A boosted classifier tree for hand shape detection
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Visual capture and understanding of hand pointing actions in a 3-D environment
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Over the past few years there has been a growing interest in visual interfaces based on gestures. Using gestures as a mean to communicate with a computer can be helpful in applications such as gaming platforms, domotic environments, augmented reality or sign language interpretation to name a few. However, a serious bottleneck for such interfaces is the current lack of accurate hand localization systems, which are necessary for tracking (re-)initialization and hand pose understanding. In fact, human hand is an articulated object with a very large degree of appearance variability which is difficult to deal with. For instance, recent attempts to solve this problem using machine learning approaches have shown poor generalization capabilities over different viewpoints and finger spatial configurations. In this article we present a model based approach to articulated hand detection which splits this variability problem by separately searching for simple finger models in the input image. A generic finger silhouette is localized in the edge map of the input image by combining curve and graph matching techniques. Cluttered backgrounds and thick textured images, which usually make it hard to compare edge information with silhouette models (e.g., using chamfer distance or voting based methods) are dealt with in our approach by simultaneously using connected curves and topological information. Finally, detected fingers are clustered using geometric constraints. Our system is able to localize in real time a hand with variable finger configurations in images with complex backgrounds, different lighting conditions and different positions of the hand with respect to the camera. Experiments with real images and videos and a simple visual interface are presented to validate the proposed method.