Using specular highlights as pose invariant features for 2D-3D pose estimation

Aaron Netz, Margarita Osadchy

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


We address the problem of 2D-3D pose estimation in difficult viewing conditions, such as low illumination, cluttered background, and large highlights and shadows that appear on the object of interest. In such challenging conditions conventional features used for establishing correspondence are unreliable. We show that under the assumption of a dominant light source, specular highlights produced by a known object can be used to establish correspondence between its image and the 3D model, and to verify the hypothesized pose. These ideas are incorporated in an efficient method for pose estimation from a monocular image of an object using only highlights produced by the object as its input. The proposed method uses no knowledge of lighting direction and no calibration object for estimating the lighting in the scene. The evaluation of the method shows good accuracy on numerous synthetic images and good robustness on real images of complex, shiny objects, with shadows and difficult backgrounds 1 .

Original languageEnglish
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
PublisherIEEE Computer Society
Number of pages8
ISBN (Print)9781457703942
StatePublished - 2011

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition


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