PublicationDetail

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

THIS WEBPAGE IS DEPRECATED - please visit our new website

B. Drost, S. Ilic
3D Object Detection and Localization Using Multimodal Point Pair Features
Second Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization & Transmission (3DIMPVT), Zurich, Switzerland, October 2012. (bib)

Object detection and localization is a crucial step for inspection and manipulation tasks in robotic and industrial applications. We present an object detection and localization scheme for 3D objects that combines intensity and depth data. A novel multimodal, scale- and rotation-invariant feature is used to simultaneously describe the object's silhouette and surface appearance. The object's position is determined by matching scene and model features via a Hough-like local voting scheme. The proposed method is quantitatively and qualitatively evaluated on a large number of real sequences, proving that it is generic and highly robust to occlusions and clutter. Comparisons with state of the art methods demonstrate comparable results and higher robustness with respect to occlusions.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.



Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif