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Title: Detecting multiple moving objects in crowded environments with coherent motion regions

Abstract

Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

Inventors:
;
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1084203
Patent Number(s):
8,462,987
Application Number:
12/489,589
Assignee:
UT-Battelle, LLC (Oak Ridge, TN)
DOE Contract Number:  
ACO5-000R22725
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Cheriyadat, Anil M., and Radke, Richard J. Detecting multiple moving objects in crowded environments with coherent motion regions. United States: N. p., 2013. Web.
Cheriyadat, Anil M., & Radke, Richard J. Detecting multiple moving objects in crowded environments with coherent motion regions. United States.
Cheriyadat, Anil M., and Radke, Richard J. 2013. "Detecting multiple moving objects in crowded environments with coherent motion regions". United States. https://www.osti.gov/servlets/purl/1084203.
@article{osti_1084203,
title = {Detecting multiple moving objects in crowded environments with coherent motion regions},
author = {Cheriyadat, Anil M. and Radke, Richard J.},
abstractNote = {Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.},
doi = {},
url = {https://www.osti.gov/biblio/1084203}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jun 11 00:00:00 EDT 2013},
month = {Tue Jun 11 00:00:00 EDT 2013}
}

Works referenced in this record:

Moving object detection in video by detecting non-Gaussian regions in subbands and active contours
conference, January 2003


Simultaneous Estimation of Segmentation and Shape
conference, January 2005


Detecting multiple moving objects in crowded environments with coherent motion regions
conference, June 2008

  • Cheriyadat, Anil M.; Bhaduri, Budhendra L.; Radke, Richard J.
  • 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops)
  • https://doi.org/10.1109/CVPRW.2008.4562983

System and method for tracking movement of objects in a scene
patent, July 2001


Visual motion analysis method for detecting arbitrary numbers of moving objects in image sequences
patent-application, November 2003