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Resolving Motion Correspondence for Densely Moving Points
January 2001 (vol. 23 no. 1)
pp. 54-72
ASCII Text
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Cor J. Veenman, Marcel J.T. Reinders, Eric Backer, "Resolving Motion Correspondence for Densely Moving Points," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 1, pp. 54-72, January, 2001.
 
 
BibTex
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@article{ 10.1109/34.899946,
author = {Cor J. Veenman and Marcel J.T. Reinders and Eric Backer},
title = {Resolving Motion Correspondence for Densely Moving Points},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {23},
number = {1},
issn = {0162-8828},
year = {2001},
pages = {54-72},
doi = {http://doi.ieeecomputersociety.org/10.1109/34.899946},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Resolving Motion Correspondence for Densely Moving Points
IS - 1
SN - 0162-8828
SP54
EP72
EPD - 54-72
A1 - Cor J. Veenman,
A1 - Marcel J.T. Reinders,
A1 - Eric Backer,
PY - 2001
KW - Motion correspondence
KW - feature point tracking
KW - target tracking
KW - algorithms.
VL - 23
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 

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—possibly constrained—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.

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Index Terms:
Motion correspondence, feature point tracking, target tracking, algorithms.
Citation:
Cor J. Veenman, Marcel J.T. Reinders, Eric Backer, "Resolving Motion Correspondence for Densely Moving Points," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 1, pp. 54-72, Jan. 2001, doi:10.1109/34.899946
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