Multiple objects tracking with HOGs matching in circular windows

Daniel Miramontes-Jaramillo, Vitaly Kober, Victor H. Diaz-Ramirez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XXXVII
EditorsAndrew G. Tescher
PublisherSPIE
ISBN (Electronic)9781628412444
DOIs
StatePublished - 2014
EventApplications of Digital Image Processing XXXVII - San Diego, United States
Duration: 18 Aug 201421 Aug 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9217
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceApplications of Digital Image Processing XXXVII
Country/TerritoryUnited States
CitySan Diego
Period18/08/1421/08/14

Keywords

  • GPU implementation
  • Histogram of oriented gradients
  • Prediction
  • Tracking

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