| 3D position, attitude and shape input using video tracking of hands and lips |
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International Conference on Computer Graphics and Interactive Techniques
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Proceedings of the 21st annual conference on Computer graphics and interactive techniques
table of contents
Pages: 185 - 192
Year of Publication: 1994
ISBN:0-89791-667-0
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Authors
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Andrew Blake
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Robotics Research Group, University of Oxford, Department of Engineering Science, University of Oxford, Parks Rd, Oxford OX1, 3PJ, UK
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Michael Isard
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Robotics Research Group, University of Oxford, Department of Engineering Science, University of Oxford, Parks Rd, Oxford OX1, 3PJ, UK
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Downloads (6 Weeks): 11, Downloads (12 Months): 97, Citation Count: 11
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ABSTRACT
Recent developments in video-tracking allow the outlines of moving, natural objects in a video-camera input stream to be tracked live, at full video-rate. Previous systems have been available to do this for specially illuminated objects or for naturally illuminated but polyhedral objects. Other systems have been able to track nonpolyhedral objects in motion, in some cases from live video, but following only centroids or key-points rather than tracking whole curves. The system described here can track accurately the curved silhouettes of moving non-polyhedral objects at frame-rate, for example hands, lips, legs, vehicles, fruit, and without any special hardware beyond a desktop workstation and a video-camera and framestore.The new algorithms are a synthesis of methods in deformable models, B-splines curve representation and control theory. This paper shows how such a facility can be used to turn parts of the body—for instance, hands and lips—into input devices. Rigid motion of a hand can be used as a 3D mouse with non-rigid gestures signalling a button press or the “lifting” of the mouse. Both rigid and non-rigid motions of lips can be tracked independently and used as inputs, for example to animate a computer-generated face.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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2
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3
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5
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Stephen Barnett. Matrices: Methods and Applications. OxfordUniversity Press, 1990.
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6
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|
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7
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|
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8
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R. Cipolla and A. Blake. The dynamic analysis of apparent contours. In Proc. 3rd Int. Conf. on Computer Vision, pages 616-625, 1990.
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9
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T.F. Cootes, C.J. Taylor, A. Lanitis, D.H. Cooper, and J. Graham. Buiding and using flexible models incorporating grey-level information. In Proc. 4th Int. Conf. on Computer Vision, pages 242-246,1993.
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10
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11
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|
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12
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M. A. Fischler andR. A. Elschlager. The representationandmatchingof pictorial structures. IEEE. Trans. Computers, C-22(1), 1973.
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13
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Arthur Gelb, editor. Applied Optimal Estimation. MIT Press, Cambridge, MA, 1974.
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14
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15
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16
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17
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M. Kass, A. Witkin, and D. Terzopoulos. Snakes: active contour models. In Proc. 1st Int. Conf. on Computer Vision, pages 259-268,1987.
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18
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J.J. Koenderink and A.J. Van Doorn. Affine structure from motion. J. Optical Soc. of America A., 8(2):337-385,1991.
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19
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20
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K. Mase and A. Pentland. Automatic lip-readingby optical flow analysis. Media Lab Report 117, MIT, 1991.
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21
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S. Menet, P. Saint-Marc, and G. Medioni. B-snakes: implementation and application to stereo. In Proceedings DARPA, pages 720-726, 1990.
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22
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23
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R. Szeliski and D. Terzopoulos. Physically-based and probabilistic modelingfor computer vision. In B. C. Vemuri, editor, Proc. SPIE 1570, Geometric Methods in Computer Vision, pages 140-152, San Diego, CA, July 1991. Society of Photo-Optical Instrumentation Engineers.
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24
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D. Terzopoulos and K. Waters. Physically-based facial modelling, analysis and animation. J. Visualization and COmputer Animation, 11(2), 1990.
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William T. Freeman , David B. Anderson , Paul A. Beardsley , Chris N. Dodge , Michal Roth , Craig D. Weissman , William S. Yerazunis , Hiroshi Kage , Kazuo Kyuma , Yasunari Miyake , Ken-ichi Tanaka, Computer Vision for Interactive Computer Graphics, IEEE Computer Graphics and Applications, v.18 n.3, p.42-53, May 1998
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