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Browsing by Author "Mogol, Ali Can"

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    Master Thesis
    3D hand reconstruction with binocular view
    (2011) Mogol, Ali Can
    In the field of Human Computer Interaction (HCI) one of the important goals is designing better interfaces for improving interactions between human beings and computers. There are lots of approaches to address this problem. One of these approaches is interfacing using human hand gestures. The capturing and modeling of the gestures and articulations of the human hand is a challenging problem. There exist hardware and software solutions proposed to solve this problem. In this thesis, an inexpensive fast and effective method to stereo capture and create 3D hand model is proposed. The setup used for this thesis is; five different color markers and commodity hardware consists of two web cameras and a low cost laptop computer. In this thesis, starting with the stereo calibration of the cameras, capturing and tracking the color markers attached to the finger tips, leading 2D points of the finger tips, converting the 2D points to 3D points and calculating the finger articulations according to these 3D points and modeling the 3D hand have been accomplished, so the user can see his/her own hand’s articulation on the screen as a 3D hand model.
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    Conference Object
    Citation - WoS: 0
    Citation - Scopus: 0
    Real-time 3D Hand Posture Reconstruction using Stereo Vision
    (Ieee, 2016) Mogol, Ali Can; Hassanpour, Reza; Hassanpour, Reza; Oztoprak, Kasim; Yazılım Mühendisliği
    One of the important goals in Human Computer Interaction (HCI) is designing better and more intuitive interfaces for improving the interactions. There are lots of approaches to address this problem. One of these approaches is utilizing human hand gestures. The degree of freedom and complex structure of human hand however, make capturing and modeling of hand gestures a challenging problem. In this paper, an inexpensive, fast, and effective method is proposed to capture 3D hand postures and gestures. An articulated 3D hand model capable of incorporating anatomical restrictions is designed. Five markers with different colors are utilized to indicate the location of finger tips in the images. The proposed method, starting with the stereo calibration of the cameras, performs capturing and tracking the color markers attached to the finger tips, reconstructing the 3D coordinates of these points, and calculating the finger articulations by applying inverse kinematics to the developed 3D hand model. The hand posture reconstruction is performed in real-time.