Advanced

Joint Random Sample Consensus and Multiple Motion Models for Robust Video Tracking

Strandmark, Petter LU and Gu, Irene (2009) Scandinavian Conference on Image Analysis (SCIA) In Lecture Notes in Computer Science 5575/2009. p.450-459
Abstract
We present a novel method for tracking multiple objects in video captured by a non-stationary camera. For low quality video, RANSAC estimation fails when the number of good matches shrinks below the minimum required to estimate the motion model. This paper extends RANSAC in the following ways: (a) Allowing multiple models of different complexity to be chosen at random; (b) Introducing a conditional probability to measure the suitability of each transformation candidate, given the object locations in previous frames; (c) Determining the best suitable transformation by the number of consensus points, the probability and the model complexity. Our experimental results have shown that the proposed estimation method better handles video of low... (More)
We present a novel method for tracking multiple objects in video captured by a non-stationary camera. For low quality video, RANSAC estimation fails when the number of good matches shrinks below the minimum required to estimate the motion model. This paper extends RANSAC in the following ways: (a) Allowing multiple models of different complexity to be chosen at random; (b) Introducing a conditional probability to measure the suitability of each transformation candidate, given the object locations in previous frames; (c) Determining the best suitable transformation by the number of consensus points, the probability and the model complexity. Our experimental results have shown that the proposed estimation method better handles video of low quality and that it is able to track deformable objects with pose changes, occlusions, motion blur and overlap. We also show that using multiple models of increasing complexity is more effective than just using RANSAC with the complex model only. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
computer vision, tracking, estimation, video
in
Lecture Notes in Computer Science
volume
5575/2009
pages
450 - 459
publisher
Springer
conference name
Scandinavian Conference on Image Analysis (SCIA)
external identifiers
  • scopus:70350628885
ISSN
0302-9743
1611-3349
DOI
10.1007/978-3-642-02230-2_46
language
English
LU publication?
yes
id
49abde9e-79a2-4abe-ab2e-83cc2da6d673 (old id 1396424)
date added to LUP
2009-05-15 15:58:10
date last changed
2017-10-22 03:37:40
@inproceedings{49abde9e-79a2-4abe-ab2e-83cc2da6d673,
  abstract     = {We present a novel method for tracking multiple objects in video captured by a non-stationary camera. For low quality video, RANSAC estimation fails when the number of good matches shrinks below the minimum required to estimate the motion model. This paper extends RANSAC in the following ways: (a) Allowing multiple models of different complexity to be chosen at random; (b) Introducing a conditional probability to measure the suitability of each transformation candidate, given the object locations in previous frames; (c) Determining the best suitable transformation by the number of consensus points, the probability and the model complexity. Our experimental results have shown that the proposed estimation method better handles video of low quality and that it is able to track deformable objects with pose changes, occlusions, motion blur and overlap. We also show that using multiple models of increasing complexity is more effective than just using RANSAC with the complex model only.},
  author       = {Strandmark, Petter and Gu, Irene},
  booktitle    = {Lecture Notes in Computer Science},
  issn         = {0302-9743},
  keyword      = {computer vision,tracking,estimation,video},
  language     = {eng},
  pages        = {450--459},
  publisher    = {Springer},
  title        = {Joint Random Sample Consensus and Multiple Motion Models for Robust Video Tracking},
  url          = {http://dx.doi.org/10.1007/978-3-642-02230-2_46},
  volume       = {5575/2009},
  year         = {2009},
}