An interactive image clipping system using hand motion recognition |
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| Affiliation: | 1. Department of Computer Science, Joongbu University, 201 Daehak-Ro, Chubu-Myeon, Kumsan-Gun, Chungnam 312-702, Republic of Korea;2. Department of Computer Science, Chungwoon University, 113 Sukgol - Ro, Nam - Gu, Incheon, 402-803, Republic of Korea;1. Eulji University, SeongNam, Republic of Korea;2. National Information Society Agency, Seoul, Republic of Korea;3. IBM Korea, Seoul, Republic of Korea;4. Rittal Korea, Seoul, Republic of Korea;5. Gwangju University, Gwangju, Republic of Korea;1. Kyung Hee University, 1 Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Republic of Korea;2. Semyung University, 579 Sinwoul-dong, Jecheon-city, Chungbuk, 390-711, Republic of Korea;1. Queensland University of Technology (QUT), Science and Engineering Faculty, Australia;2. University of Vienna, Faculty of Computer Science, Austria;3. Metasonic GmbH, Munchner Strasse 29 - Hettenshausen, 85276 Phaffenhofen, Germany;1. School of Information, Zhejiang University of Finance & Economics, China;2. Department of Computer Science, The University of Auckland, New Zealand;3. College of Computer Science, Inner Mongolia University, China;4. School of Engineering, Auckland University of Technology, New Zealand |
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| Abstract: | We present an efficient hand recognition algorithm for an interactive image clipping system, which is widely used for environments such as public facilities and security environments where personal capturing devices including mobile phones are not allowed. User-friendly interface and accurate image capturing function are required for an image clipping system. We build the system by combining Microsoft Kinect, HD webcam and projector. The Kinect and webcam are used to capture the motions of users׳ hand and project is to display the user-selected area from the capturing material. Hand recognition is composed of three steps: (i) the region occupied by users׳ hand is extracted from an image, (ii) the fingertips of the extracted hand region are analyzed using k-curvature algorithm, and (iii) the height of the fingertip is estimated using the depth image from Kinect. The height of the fingertip informs whether users׳ finger touched the surface of the target. The region captured by the fingertip is clipped from the image and stored as the target image. The excellence of our hand recognition algorithm is proved through a user test. |
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| Keywords: | Image clipping Hand recognition Region recognition Kinect |
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