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
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Real-Time Hand Detection and Gesture Tracking with GMM and Model Adaptation
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
A visual system for hand gesture recognition in human-computer interaction
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Eye tracking using neural network and mean-shift
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Bimanual natural user interaction for 3D modelling application using stereo computer vision
Proceedings of the 13th International Conference of the NZ Chapter of the ACM's Special Interest Group on Human-Computer Interaction
Intuitive substitute interface
Personal and Ubiquitous Computing
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Abstract: This paper describes an algorithm to detect and track A hand in each image taken by a wearable camera. We primarily use color information, however, instead of predefined skin-color models, we dynamically construct hand- and background-color models by using a Gaussian mixture model to approximate the color histogram. Not only to obtain the estimated mean of hand color necessary for the restricted EM algorithm that estimates the GMM but to classify hand pixels based on the Bayes decision theory, we use a spatial probability distribution of hand pixels. Because the static distribution is inadequate for the hand-tracking stage, we translate the distribution with the hand motion based on the mean shift algorithm. Using the proposed method, we implemented the Hand Mouse, that uses the wearer's hand as a pointing device, on our Wearable Vision System.