Image-Based Reconstruction for View-Independent Human Motion Recognition

Robert Bodor, Bennett Jackson, Osama Masoud, Nikolaos P Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

In this paper, we introduce a novel method for employing image-based rendering to extend the range of use of human motion recognition systems. We demonstrate the use of image-based rendering to generate additional training sets for view-dependent human motion recognition systems. Input views orthogonal to the direction of motion are created automatically to construct the proper view from a combination of non-orthogonal views taken from several cameras. To extend motion recognition systems, image-based rendering can be utilized in two ways: (i) to generate additional training sets for these systems containing a large number of nonorthogonal views, and (ii) to generate orthogonal views (the views those systems are trained to recognize) from a combination of non-orthogonal views taken from several cameras. In this case, image-based rendering is used to generate views orthogonal to the mean direction of motion. We tested the method using an existing viewdependent human motion recognition system on two different sequences of motion, and promising initial results were obtained.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Intelligent Robots and Systems
Pages1548-1553
Number of pages6
Volume2
StatePublished - Dec 26 2003
Event2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States
Duration: Oct 27 2003Oct 31 2003

Other

Other2003 IEEE/RSJ International Conference on Intelligent Robots and Systems
CountryUnited States
CityLas Vegas, NV
Period10/27/0310/31/03

Keywords

  • Computer vision
  • Human motion recognition
  • Image-based rendering
  • Shape reconstruction
  • Visual tracking

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