Title :
Higher Order Matching for Consistent Multiple Target Tracking
Author :
Arora, Chetan ; Globerson, Amir
Abstract :
This paper addresses the data assignment problem in multi frame multi object tracking in video sequences. Traditional methods employing maximum weight bipartite matching offer limited temporal modeling. It has recently been shown [6, 8, 24] that incorporating higher order temporal constraints improves the assignment solution. Finding maximum weight matching with higher order constraints is however NP-hard and the solutions proposed until now have either been greedy [8] or rely on greedy rounding of the solution obtained from spectral techniques [15]. We propose a novel algorithm to find the approximate solution to data assignment problem with higher order temporal constraints using the method of dual decomposition and the MPLP message passing algorithm [21]. We compare the proposed algorithm with an implementation of [8] and [15] and show that proposed technique provides better solution with a bound on approximation factor for each inferred solution.
Keywords :
approximation theory; image matching; image sequences; message passing; object tracking; target tracking; video signal processing; MPLP message passing algorithm; approximation factor; consistent multiple target tracking; data assignment problem; dual decomposition; higher order matching; higher order temporal constraints; maximum weight matching; multiframe multiobject tracking; video sequences; Approximation algorithms; Approximation methods; Computer vision; Educational institutions; Smoothing methods; Trajectory; Upper bound;
Conference_Titel :
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location :
Sydney, VIC
DOI :
10.1109/ICCV.2013.29