Human-computer interaction through time-of-flight and RGB cameras
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
An interaction system using mixed hand gestures
Proceedings of the 10th asia pacific conference on Computer human interaction
Improving of gesture recognition using multi-hypotheses object association
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
TV remote control using human hand motion based on optical flow system
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Hand posture recognition from disparity cost map
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Toward a 3D body part detection video dataset and hand tracking benchmark
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
A survey of human motion analysis using depth imagery
Pattern Recognition Letters
A method for hand detection using internal features and active boosting-based learning
Proceedings of the Fourth Symposium on Information and Communication Technology
Real-time Hand Gesture Recognition from Depth Images Using Convex Shape Decomposition Method
Journal of Signal Processing Systems
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Time-of-Flight (ToF) and other IR-based cameras that register depth are becoming more and more affordable in consumer electronics. This paper aims to improve a realtime hand gesture interaction system by augmenting it with a ToF camera. First, the ToF camera and the RGB camera are calibrated, and a mapping is made from the depth data to the RGB image. Then, a novel hand detection algorithm is introduced based on depth and color. This not only improves detection rates, but also allows for the hand to overlap with the face, or with hands from other persons in the background. The hand detection algorithm is evaluated in these settings, and compared to previous algorithms. Furthermore, the depth information allows us to track the position of the hand in 3D, allowing for more interesting modes of interaction. Finally, the hand gesture recognition algorithm is applied to the depth data as well, and compared to the recognition based on the RGB images. The result is a real-time hand gesture interaction system that allows for complex 3D gestures and is not disturbed by objects or persons in the background.