VizWear: Toward Human-Centered Interaction through Wearable Vision and Visualization
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Bare-hand human-computer interaction
Proceedings of the 2001 workshop on Perceptive user interfaces
Robust finger tracking for wearable computer interfacing
Proceedings of the 2001 workshop on Perceptive user interfaces
Skin Color-Based Video Segmentation under Time-Varying Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
An adaptive skin model and its application to objectionable image filtering
Proceedings of the 12th annual ACM international conference on Multimedia
Skin Segmentation Using Color Pixel Classification: Analysis and Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
Browsing the environment with the SNAP&TELL wearable computer system
Personal and Ubiquitous Computing
Iterative Local-Global Energy Minimization for Automatic Extraction of Objects of Interest
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of skin-color modeling and detection methods
Pattern Recognition
Resolving hand over face occlusion
Image and Vision Computing
The catchment feature model: a device for multimodal fusion and a bridge between signal and sense
EURASIP Journal on Applied Signal Processing
AFRIGRAPH '07 Proceedings of the 5th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa
CBIR approach to the recognition of a sign language alphabet
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
Robust hand tracking using a simple color classification technique
VRCAI '08 Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
Sign recognition using constrained optimization
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Adaptive learning of an accurate skin-color model
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Hand gesture recognition using depth data
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: interaction techniques and environments - Volume Part II
Vision-Based recognition of hand shapes in taiwanese sign language
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Resolving hand over face occlusion
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
Experiments with computer vision methods for hand detection
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
A comparative study on face detection and tracking algorithms
Expert Systems with Applications: An International Journal
A modular approach to gesture recognition for interaction with a domestic service robot
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
A method for hand detection using internal features and active boosting-based learning
Proceedings of the Fourth Symposium on Information and Communication Technology
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Color has been widely used for hand segmentation. However, many approaches rely on predefined skin color models. It is very difficult to predefine a color model in a mobile application where the light condition may change dramatically over time. In this paper, we propose a novel statistical approach to hand segmentation based on Bayes decision theory. The proposed method requires no predefined skin color model. Instead it generates a hand color model and a background color model for a given image, and uses these models to classify each pixel in the image as either a hand pixel or a background pixel. Models are generated using a Gaussian mixture model with the restricted EM algorithm. This method is capable of segmenting hands of arbitrary color in a complex scene. It performs well even when there is a significant overlap between hand and background colors, or when the user wears gloves. We show that the Bayes decision method is superior to a commonly used method by comparing their upper bound performance. Experimental results demonstrate the feasibility of the proposed method.