Resolving Motion Correspondence for Densely Moving Points

  • Authors:

  • Cor J. Veenman;Marcel J. T. Reinders;Eric Backer

  • Affiliations:

  • Delft Univ. of Technology, Delft, The Netherlands;Delft Univ. of Technology, Delft, The Netherlands;Delft Univ. of Technology, Delft, The Netherlands

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 2001

Quantified Score

Hi-index 0.15

Visualization

Abstract

This paper studies the motion correspondence problem for which a diversity of qualitative and statistical solutions exist. We concentrate on qualitative modeling, especially in situations where assignment conflicts arise either because multiple features compete for one detected point or because multiple detected points fit a single feature point. We leave out the possibility of point track initiation and termination because that principally conflicts with allowing for temporary point occlusion. We introduce individual, combined, and global motion models and fit existing qualitative solutions in this framework. Additionally, we present a new efficient tracking algorithm that satisfies these驴possibly constrained驴models in a greedy matching sense, including an effective way to handle detection errors and occlusion. The performance evaluation shows that the proposed algorithm outperforms existing greedy matching algorithms. Finally, we describe an extension to the tracker that enables automatic initialization of the point tracks. Several experiments show that the extended algorithm is efficient, hardly sensitive its few parameters, and qualitatively better than other algorithms, including the presumed optimal statistical multiple hypothesis tracker.