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Titlebook: Consumer Depth Cameras for Computer Vision; Research Topics and Andrea Fossati,Juergen Gall,Kurt Konolige Book 2013 Springer-Verlag London

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RGB-D Object Recognition: Features, Algorithms, and a Large Scale Benchmarknts. The dataset has been made publicly available to the research community so as to enable rapid progress based on this promising technology. We describe the dataset collection procedure and present techniques for RGB-D object recognition and detection of objects in scenes recorded using RGB-D vide
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Studies in Contemporary Economicsseful features from range images is addressed. There has been much success in using the histogram of oriented gradients (HOG) as a global descriptor for object detection in intensity images. There are also many proposed descriptors designed specifically for depth data (spin images, shape context, et
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https://doi.org/10.1007/978-3-642-83455-4nts. The dataset has been made publicly available to the research community so as to enable rapid progress based on this promising technology. We describe the dataset collection procedure and present techniques for RGB-D object recognition and detection of objects in scenes recorded using RGB-D vide
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3D with Kinectarison of Kinect accuracy with stereo reconstruction from SLR cameras and a 3D-TOF camera. We propose a Kinect geometrical model and its calibration procedure providing an accurate calibration of Kinect 3D measurement and Kinect cameras. We compare our Kinect calibration procedure with its alternati
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