A Real-Time Continuous Gesture Recognition System for Sign Language
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Recognition of Local Features for Camera-Based Sign Language Recognition System
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Australian sign language recognition
Machine Vision and Applications
Resolving hand over face occlusion
Image and Vision Computing
Robust Tracking for Processing of Videos of Communication's Gestures
Gesture-Based Human-Computer Interaction and Simulation
Segmentation of the face and hands in sign language video sequences using color and motion cues
IEEE Transactions on Circuits and Systems for Video Technology
GW'11 Proceedings of the 9th international conference on Gesture and Sign Language in Human-Computer Interaction and Embodied Communication
Hand detection and feature extraction for static Thai Sign Language recognition
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
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This paper presents a method to accurately segment the hand over the face. The similarity of colours and the important variability of the hand shape make it challenging. We propose a method based on the combination of two features: pixel colour and edges orientation. First, a specific skin model is used to find, before occlusion, the face position and the face template. Then, during occlusion the face template is registered using local gradient orientations to track the face position. Colour information is extracted from changes on pixel colours and edges are classified as belonging to the hand or to the face by mapping edges orientation to the face template. Finally by merging both features and by using an hysteresis threshold, which considers connectivity, a robust hand segmentation is reached. Experiments were performed using the Dicta-Sign corpus and showed the versatility of the proposed approach.