Cue circles: image feature for measuring 3-D motion of articulated objects using sequential image pair

The shape of articulated objects such as the human body can be simplified into a stick model which is represented by connections of several circular generalized cylinders (GCs). The authors propose a new image feature called cue circles (CCs), and present a method for obtaining CCs from input images. Using CCs, 3D motion of the human body is measured from a sequence of boundary contour image pairs, which is obtained by an active binocular sensor system. The body model used is represented by a set of cue spheres (CSs), each of which is located at ends of GCs. Stereo matching for recovering the body model is carried out by finding pairs of CCs between the pair of contour images under consideration: a CS is projected on the two image planes as its corresponding CCs.

[1]  Aaron F. Bobick,et al.  Recognition of human body motion using phase space constraints , 1995, Proceedings of IEEE International Conference on Computer Vision.

[2]  Jae-Moon Chung,et al.  Extraction of parametric descriptions of circular GCS from a pair of contours for 3-D shape recognition , 1996, Pattern Recognit..

[3]  Dimitris N. Metaxas,et al.  Tracking nonrigid 3D objects , 1993 .

[4]  Jae-Moon Chung,et al.  Extracting parametric descriptions of circular GCs from a pair of contours for 3-D shapes recognition , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[5]  T. Nishimura,et al.  Spotting recognition of human gestures from time-varying images , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[6]  Junji Yamato,et al.  Recognizing human action in time-sequential images using hidden Markov model , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Alex Pentland,et al.  Recovery of non-rigid motion and structure , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Jae-Moon Chung,et al.  Measuring human actions using sequential boundary contour pairs , 1996, Proceedings 5th IEEE International Workshop on Robot and Human Communication. RO-MAN'96 TSUKUBA.

[9]  Ioannis A. Kakadiaris,et al.  3D human body model acquisition from multiple views , 1995, Proceedings of IEEE International Conference on Computer Vision.

[10]  Trevor Darrell,et al.  Active face tracking and pose estimation in an interactive room , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Noboru Ohnishi,et al.  Robust Matching and Hierarchical Recognition of 2-D Shapes Using "Chain of Circles" , 1998, ACCV.

[12]  Eli Hagen,et al.  Towards an American Sign Language interface , 1994, Artificial Intelligence Review.

[13]  Alex Pentland,et al.  Pfinder: real-time tracking of the human body , 1996, Other Conferences.

[14]  Thomas S. Huang,et al.  Vision based hand modeling and tracking for virtual teleconferencing and telecollaboration , 1995, Proceedings of IEEE International Conference on Computer Vision.

[15]  Jae-Moon Chung,et al.  Binocular vision planning with anthropomorphic features for grasping parts by robots , 1996, Robotica.

[16]  L. Davis,et al.  el-based tracking of humans in action: , 1996 .

[17]  Alan L. Yuille,et al.  FORMS: A flexible object recognition and modelling system , 1995, Proceedings of IEEE International Conference on Computer Vision.

[18]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[19]  J. O'Rourke,et al.  A spherical representation of a human body for visualizing movement , 1979, Proceedings of the IEEE.

[20]  Pietro Perona,et al.  Monocular tracking of the human arm in 3D , 1995, Proceedings of IEEE International Conference on Computer Vision.

[21]  Ioannis A. Kakadiaris,et al.  Model-based estimation of 3D human motion with occlusion based on active multi-viewpoint selection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[22]  Aaron F. Bobick,et al.  A state-based technique for the summarization and recognition of gesture , 1995, Proceedings of IEEE International Conference on Computer Vision.

[23]  Alex Pentland,et al.  Recovery of Nonrigid Motion and Structure , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Takeo Kanade,et al.  Model-based tracking of self-occluding articulated objects , 1995, Proceedings of IEEE International Conference on Computer Vision.

[25]  J. O'Rourke,et al.  Model-based image analysis of human motion using constraint propagation , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Noboru Ohnishi,et al.  Chain of Circles for Matching and Recognition of Planar Shapes , 1997, IJCAI.