Computer vision and machine learning with rgb-d sensors / edited by Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang.
Tipo de material:
TextoSeries Advances in Computer Vision and Pattern RecognitionEditor: Cham : Springer International Publishing : Springer, 2014Descripción: x, 316 páginas : 163 ilustraciones, 148 ilustraciones en colorTipo de contenido: - texto
- computadora
- recurso en línea
- 9783319086514
- TA1637-1638
Springer eBooks
Part I: Surveys -- 3D Depth Cameras in Vision: Benefits and Limitations of the Hardware -- A State-of-the-Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets -- Part II: Reconstruction, Mapping and Synthesis -- Calibration Between Depth and Color Sensors for Commodity Depth Cameras -- Depth Map Denoising via CDT-Based Joint Bilateral Filter -- Human Performance Capture Using Multiple Handheld Kinects -- Human Centered 3D Home Applications via Low-Cost RGBD Cameras -- Matching of 3D Objects Based on 3D Curves -- Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinects -- Part III: Detection, Segmentation and Tracking -- RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons -- RGB-D Human Identification and Tracking in a Smart Environment -- Part IV: Learning-Based Recognition -- Feature Descriptors for Depth-Based Hand Gesture Recognition -- Hand Parsing and Gesture Recognition with a Commodity Depth Camera -- Learning Fast Hand Pose Recognition -- Real time Hand-Gesture Recognition Using RGB-D Sensor.
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