Title :
Multitarget data association with higher-order motion models
Author :
Collins, Robert T.
Author_Institution :
Pennsylvania State Univ., University Park, PA, USA
Abstract :
We present an iterative approximate solution to the multidimensional assignment problem under general cost functions. The method maintains a feasible solution at every step, and is guaranteed to converge. It is similar to the iterated conditional modes (ICM) algorithm, but applied at each step to a block of variables representing correspondences between two adjacent frames, with the optimal conditional mode being calculated exactly as the solution to a two-frame linear assignment problem. Experiments with ground-truthed trajectory data show that the method outperforms both network-flow data association and greedy recursive filtering using a constant velocity motion model.
Keywords :
approximation theory; image processing; iterative methods; sensor fusion; constant velocity motion model; general cost function; ground-truthed trajectory data; higher-order motion model; iterative approximate solution; multidimensional assignment problem; multitarget data association; two-frame linear assignment problem; Approximation algorithms; Cost function; Indexes; Kinematics; Target tracking; Trajectory;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-1226-4
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2012.6247870