Monocular tracking of the human arm in 3D

We address the problem of estimating the position and motion of a human arm in 3D without any constraints on its behavior and without the use of special markers. We model the arm as two truncated right-circular cones connected with spherical joints. We propose to use a recursive estimator for arm position, and to provide the estimator with error signals obtained by comparing the projected estimated arm position with that of the actual arm in the image. The system is demonstrated and tested on a real image sequence.<<ETX>>

[1]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[2]  R. Bucy.  Nonlinear filtering theory , 1965 .

[3]  A. Jazwinski.  Stochastic Processes and Filtering Theory , 1970 .

[4]  Alain Bensoussan,et al.  Non linear filtering theory , 1990 .

[5]  Giancarlo Ferrigno,et al.  ELITE: A goal oriented vision system for moving objects detection , 1991, Robotica.

[6]  Karl Rohr,et al.  Incremental recognition of pedestrians from image sequences , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[7]  E. Adelson,et al.  Analyzing gait with spatiotemporal surfaces , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.

[8]  Takeo Kanade,et al.  DigitEyes: vision-based hand tracking for human-computer interaction , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.