The Information-Form Data Association Filter
Schumitsch, Brad, Thrun, Sebastian, Bradski, Gary, Olukotun, Kunle
–Neural Information Processing Systems
This paper presents a new filter for online data association problems in high-dimensional spaces. The key innovation is a representation of the data association posterior in information form, in which the "proximity" ofobjects and tracks are expressed by numerical links. Updating these links requires linear time, compared to exponential time required for computing the exact posterior probabilities. The paper derives the algorithm formally and provides comparative results using data obtained by a real-world camera array and by a large-scale sensor network simulation.
Neural Information Processing Systems
Dec-31-2006