Hand Gesture Recognition Using Computer Vision Techniques - Muazzam, Hassam
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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.

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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
Hassam Muazzam received his Bachelors in Electrical Engineering from University of the Punjab and Masters in Electrical Engineering from Government College University.He is currently working as a Lecturer at Department of Electrical Engineering,University of the Punjab,Lahore,Pakistan.