Pose Estimation using a Hierarchical 3D Representation of Contours and Surfaces

Anders Glent Buch, Dirk Kraft, Joni-Kristian Kämäräinen, Norbert Krüger

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


We present a system for detecting the pose of rigid objects using texture and contour information. From a stereo image view of a scene, a sparse hierarchical scene representation is reconstructed using an early cognitive vision system. We define an object model in terms of a simple context descriptor of the contour and texture features to provide a sparse, yet descriptive object representation. Using our descriptors, we do a search in the correspondence space to perform outlier removal and compute the object pose. We perform an extensive evaluation of our approach with stereo images of a variety of real-world objects rendered in a controlled virtual environment. Our experiments show the complementary role of 3D texture and contour information allowing for pose estimation with high robustness and accuracy.
Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Computer Vision Theory and Applications
PublisherSCITEPRESS Digital Library
Publication date2013
ISBN (Print)978-989-8565-47-1
Publication statusPublished - 2013
EventInternational Conference on Computer Vision Theory and Applications - Barcelona, Spain
Duration: 21. Feb 201324. Feb 2013


ConferenceInternational Conference on Computer Vision Theory and Applications


  • Early cognitive vision
  • Pose estimation
  • Shape context descriptors

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