Object rigidity and reflectivity identification based on motion analysis

Di Zang, Paul R Schrater, Katja Doerschner

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

4 Scopus citations

Abstract

Rigidity and reflectivity are important properties of objects, identifying these properties is a fundamental problem for many computer vision applications like motion and tracking. In this paper, we extend our previous work to propose a motion analysis based approach for detecting the object's rigidity and reflectivity. This approach consists of two steps. The first step aims to identify object rigidity based on motion estimation and optic flow matching. The second step is to classify specular rigid and diffuse rigid objects using structure from motion and Procrustes analysis. We show how rigid bodies can be detected without knowing any prior motion information by using a mutual information based matching method. In addition, we use a statistic way to set thresholds for rigidity classification. Presented results demonstrate that our approach can efficiently classify the rigidity and reflectivity of an object.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages4573-4576
Number of pages4
DOIs
StatePublished - Dec 1 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: Sep 26 2010Sep 29 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong
Period9/26/109/29/10

Keywords

  • Mutual information
  • Optic flow
  • Reflectivity
  • Rigidity

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