Robust fingertip detection in a complex environment - 2016 PROJECT TITLE : Robust fingertip detection in a complex environment - 2016 ABSTRACT: Fingertip detection includes a broad application in gesture recognition and finger tracking. It is conjointly an vital foundation of human-pc interaction systems. However, most algorithms are appropriate for straightforward conditions with low accuracy because the hand could be a nonrigid object, and its look model is advanced. To deal with the challenging downside of accurately detecting fingertips in a very advanced environment, we propose a unique and strong fingertip detection algorithm during this paper. In contrast to existing ways, our study requires no special device or mark, and users are free to move their hands. Via dense optical flow and a skin filter, we tend to perform complete hand region segmentation in a very complicated surroundings. We find the most worth of the native centroid distance outside the centroid circles and determine fingertips. Our algorithm performs favorably compared with common hand region segmentation and fingertip detection methods. Thorough experimentation proves that our proposed algorithm is effective and robust. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Image Segmentation Image Sequences Object Detection Human Computer Interaction Fingertip Detection Hand Appearance Model Hand Region Segmentation Reversible data hiding in encrypted images based on progressive recovery - 2016 Learning a combined model of visual Saliency for fixation prediction - 2016
