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This paper presents a marker-less two-hand gesture recognition system based on Kinect. Using the depth and skeleton from Kinect, mark-less hand extraction is achieved. Finger Earth Mover's Distance (FEMD) is then applied as the measurement to recognize the gestures, with the help of a new morphological finger extraction method. A two-hand based user interface is designed and implemented to provide...
Depth map estimation is an active and long standing problem in image/video processing and computer vision. Conventional depth estimation algorithms which rely on stereo/multi-view vision or depth sensing devices alone are limited by complicated scenes or imperfections of the depth sensing devices. On the other hand, the depth maps obtained from the stereo/multi-view vision and depth sensing devices...
This paper presents a novel hand gesture recognition algorithm based on Kinect. Using the depth and skeleton from Kinect, mark-less hand extraction is achieved. The hand shapes (depth) and corresponded textures (color) are represented in the form of superpixels, which better retain the overall shapes and color of the gestures to be recognized. Based on this representation, a novel distance metric,...
Depth map estimation is a classical problem in computer vision. Conventional depth estimation relies on stereo/multi-view matching or depth sensing devices alone. In this paper, we propose a system which addresses high resolution and high quality depth estimation based on joint fusion of stereo and Kinect data. The problem is formulated as a maximum a posteriori probability (MAP) estimation problem...
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