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An endeavor has been made with the help of computer vision techniques and the release of Microsoft Kinect camera. The task of segmentation has been implemented using RGB with depth information; to enhance it, YCbCr color scheme is used. Two level feature extraction algorithms are examined, Scale Invariant Feature Transform (SIFT) for RGB images and the Gradient kernel descriptor method for depth images. Finally, Support Vector Machine (SVM) and K- nearest neighbor (K-NN) are tested.

Produktbeschreibung
An endeavor has been made with the help of computer vision techniques and the release of Microsoft Kinect camera. The task of segmentation has been implemented using RGB with depth information; to enhance it, YCbCr color scheme is used. Two level feature extraction algorithms are examined, Scale Invariant Feature Transform (SIFT) for RGB images and the Gradient kernel descriptor method for depth images. Finally, Support Vector Machine (SVM) and K- nearest neighbor (K-NN) are tested.
Autorenporträt
L'Ing. Hassam Muazzam ha conseguito la laurea in ingegneria elettrica presso l'Università del Punjab e il master in ingegneria elettrica presso la Government College University. Attualmente lavora come docente presso il Dipartimento di Ingegneria Elettrica dell'Università del Punjab, Lahore, Pakistan.