ProjectComputerVisionCADModel

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Vision Targeted CAD Models

Vision Targeted CAD Models

In academic collaboration with:
Dr. Vincent Lepetit, EPFL, Lausanne Switzerland

Scientific Director: Selim Benhimane and Nassir Navab

Contact Person(s): Stefan Hinterstoisser

Keywords: Computer Vision, Industrial Augmented Reality

Abstract

This project investigates vision features and their intelligent application on known CAD models for pose estimation. The advantage of combining CAD models and vision features lies in the known 3D geometry of the CAD model. Exemplary vision features are e.g. SIFT features, Randomized Trees, SURF features and other well known methods. The main goal is to use such an extended CAD model for pose estimation and for tracking initialization.

Detailed Project Description

Natural 3D Markers (N3M): A first step towards vision features incorporating 3D-CAD models was made by creating Natural 3D Markers (N3Ms). N3Ms are minimal subsets of vision features which are learned during a training step from a 3D-CAD model and which are carefully designed to guarantee fast detection and quasi optimal pose estimation. N3Ms lead to high invariance to partial occlusion, high invariance to cluttered backgrounds, fast outlier elimination and the absence of ill-conditioned point configurations (e.g. collinear points) in the detection and pose estimation process. The results were published at ICCV 2007 in Rio de Janeiro.
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The detection and pose estimations runs with about 15fps.

Videos

Tracking by Detection with Leopar

4 matched points are enough to detect their correct classification

Tracking (ESM) and N3Ms unified.

Publications

2012
S. Hinterstoisser, C. Cagniart, S. Ilic, P. Sturm, N. Navab, P. Fua, V. Lepetit
Gradient Response Maps for Real-Time Detection of Texture-Less Objects
IEEE Transactions on Pattern Analysis and Maschine Intelligence (TPAMI). (bib)
2011
J. Bohren, R. B. Rusu, E. G. Jones, E. Marder-Eppstein, C. Pantofaru, M. Wise, L. Mösenlechner, W. Meeussen, S. Holzer
Towards Autonomous Robotic Butlers: Lessons Learned with the PR2
2011 IEEE International Conference on Robotics and Automation, Shanghai, China, May 2011. (bib)
S. Hinterstoisser, S. Holzer, C. Cagniart, S. Ilic, K. Konolige, N. Navab, V. Lepetit
Multimodal Templates for Real-Time Detection of Texture-less Objects in Heavily Cluttered Scenes (Oral)
IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain, November 2011. (bib)
S. Hinterstoisser, V. Lepetit, S. Benhimane, P. Fua, N. Navab
Learning Real-Time Perspective Patch Rectification
International Journal of Computer Vision (IJCV), Springer Verlag, The final publication is available at www.springerlink.com (bib)
2010
S. Holzer, S. Ilic, N. Navab
Adaptive Linear Predictors for Real-Time Tracking
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, California (USA), June 2010. (bib)
N. Alt, S. Hinterstoisser, N. Navab
Rapid Selection of Reliable Templates for Visual Tracking
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, California (USA), June 2010. (bib)
S. Hinterstoisser, V. Lepetit, S. Ilic, P. Fua, N. Navab
Dominant Orientation Templates for Real-Time Detection of Texture-Less Objects
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, California (USA), June 2010. (bib)
2009
S. Hinterstoisser, O. Kutter, N. Navab, P. Fua, V. Lepetit
Real-Time Learning of Accurate Patch Rectification (Oral Presentation)
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Florida (USA), June 2009. (bib)
S. Holzer, S. Hinterstoisser, S. Ilic, N. Navab
Distance Transform Templates for Object Detection and Pose Estimation
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Florida (USA), June 2009. (bib)
2008
S. Hinterstoisser, S. Benhimane, V. Lepetit, P. Fua, N. Navab
Simultaneous Recognition and Homography Extraction of Local Patches with a Simple Linear Classifier
British Machine Vision Conference (BMVC), Leeds (UK), September 1-4, 2008 (bib)
S. Hinterstoisser, S. Benhimane, N. Navab, P. Fua, V. Lepetit
Online Learning of Patch Perspective Rectification for Efficient Object Detection
IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska (USA), June 2008. (bib)
2007
S. Hinterstoisser, S. Benhimane, N. Navab
N3M: Natural 3D Markers for Real-Time Object Detection and Pose Estimation
IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, October 14-20, 2007 (bib)

Team

Contact Person(s)

Stefan Hinterstoisser
Dr. Stefan Hinterstoisser

Working Group

Nassir Navab
Prof. Dr. Nassir Navab
Selim Benhimane
Dr. Eng. Selim Benhimane

Location



Technische Universität München
Institut für Informatik / I16
Boltzmannstr. 3
85748 Garching bei München

Tel.: +49 89 289-17058
Fax: +49 89 289-17059
Visit our lab at Garching.



internal project page

Please contact Stefan Hinterstoisser for available student projects within this research project.

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