Joint Random Sample Consensus and Multiple Motion Models for Robust Video Tracking
(2009) Scandinavian Conference on Image Analysis (SCIA) 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:
https://lup.lub.lu.se/record/1396424
- author
- Strandmark, Petter LU and Gu, Irene
- organization
- publishing date
- 2009
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- computer vision, tracking, estimation, video
- host publication
- Lecture Notes in Computer Science
- volume
- 5575/2009
- pages
- 450 - 459
- publisher
- Springer
- conference name
- Scandinavian Conference on Image Analysis (SCIA)
- conference location
- Oslo, Norway
- conference dates
- 2009-06-15
- 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
- 2016-04-01 11:46:25
- date last changed
- 2024-01-07 19:56:39
@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}},
keywords = {{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}},
doi = {{10.1007/978-3-642-02230-2_46}},
volume = {{5575/2009}},
year = {{2009}},
}