Predictive tracking of targets using image sequences
J Frau, V Llario - Proceedings IROS'91: IEEE/RSJ International …, 1991 - ieeexplore.ieee.org
J Frau, V Llario
Proceedings IROS'91: IEEE/RSJ International Workshop on …, 1991•ieeexplore.ieee.orgA near-real time, highly efficient and robust visual tracking system for multiple moving
objects using image sequences taken from a stationary or moving camera is presented. The
module provides an estimate of the translational and rotational target positions on the image
plane based on the self-management order paradigm (SMOP). This technique deals with the
motion estimation from regression analysis as well as the estimation of the optimum order of
the motion model from sample to sample. Finally, SMOP allows one to predict the next …
objects using image sequences taken from a stationary or moving camera is presented. The
module provides an estimate of the translational and rotational target positions on the image
plane based on the self-management order paradigm (SMOP). This technique deals with the
motion estimation from regression analysis as well as the estimation of the optimum order of
the motion model from sample to sample. Finally, SMOP allows one to predict the next …
A near-real time, highly efficient and robust visual tracking system for multiple moving objects using image sequences taken from a stationary or moving camera is presented. The module provides an estimate of the translational and rotational target positions on the image plane based on the self-management order paradigm (SMOP). This technique deals with the motion estimation from regression analysis as well as the estimation of the optimum order of the motion model from sample to sample. Finally, SMOP allows one to predict the next location of the target on the image plane and to constrain the zone of the image where the recognition algorithm has to be applied.< >
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