Thermal Face Recognition Over Time
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Recent advances in visual and infrared face recognition: a review
Computer Vision and Image Understanding
IR and visible light face recognition
Computer Vision and Image Understanding
Robust hand tracking in realtime using a single head-mounted RGB camera
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: interaction modalities and techniques - Volume Part IV
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In this paper, we present our results to build an automatic gesture recognition system using different types of cameras to compare them in reference to their features for segmentation. Normally, the images of a mono color camera system are mostly used as input data in the research area of gesture recognition. In comparison to that, the analysis results of a stereo color camera and a thermal camera system are used to determine the advantages and disadvantages of these camera systems. With this basics, a real-time gesture recognition system is build to classify alphabets (A-Z) and numbers (0-9) with an average recognition rate of 98% using Hidden Markov Models (HMM).