Application of Affine-Invariant Fourier Descriptors to Recognition of 3-D Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
The Hand Mouse: GMM Hand-Color Classication and Mean Shift Tracking
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 Hand Shape Recognition for Human Interface
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Bare-hand human-computer interaction
Proceedings of the 2001 workshop on Perceptive user interfaces
Visual touchpad: a two-handed gestural input device
Proceedings of the 6th international conference on Multimodal interfaces
A Robust Hand Tracking for Gesture-Based Interaction of Wearable Computers
ISWC '04 Proceedings of the Eighth International Symposium on Wearable Computers
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Um sistema de interação baseado em gestos manuais tridimensionais para ambientes virtuais
Proceedings of the IX Symposium on Human Factors in Computing Systems
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Visual hand gestures offer an interesting modality for Human-Computer-Interaction (HCI) applications. Gesture recognition and hand tracking, however, are not trivial tasks and real environments set a lot of challenges to algorithms performing such activities. In this paper, a novel combination of techniques is presented for tracking and recognition of hand gestures in real, cluttered environments. In addition to combining existing techniques, a method for locating a hand and segmenting it from an arm in binary silhouettes and a foreground model for color segmentation is proposed. A single hand is tracked with a single camera and the trajectory information is extracted along with recognition of five different gestures. This information is exploited for replacing the operations of a normal computer mouse. The silhouette of the hand is extracted as a combination of different segmentation methods: An adaptive colour model based segmentation is combined with intensity and chromaticity based background subtraction techniques to achieve robust performance in cluttered scenes. An affine-invariant Fourier-descriptor is derived from the silhouette, which is then classified to a hand shape class with support vector machines (SVM). Gestures are recognized as changes in the hand shape with a finite state machine (FSM).