ICRA'09 Paper Abstract


Paper FrC2.3

Klank, Ulrich (Technische Universität München), Zia, Muhammad Zeeshan (Technische Universität München), Beetz, Michael (Technische Universität München)

3D Model Selection from an Internet Database for Robotic Vision

Scheduled for presentation during the Regular Sessions "Computer Vision for Robotics and Automation - IV" (FrC2), Friday, May 15, 2009, 14:10−14:30, Room: ICR

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 24, 2022

Keywords Computer Vision for Robotics and Automation, Visual Servoing, Recognition


We propose a new method for automatically accessing an Internet database of 3D models that are searchable only by their user-annotated labels, for using them for vision and robotic manipulation purposes. Instead of having only a local database containing already seen objects, we want to use shared databases available over the Internet. This approach while having the potential to dramatically increase the visual recognition capability of robots, also poses certain problems, like wrong annotation due to the open nature of the database, or overwhelming amounts of data (many 3D models) or the lack of relevant data (no models matching a specified label). To solve those problems we propose the following: First, we present an outlier/inlier classification method for reducing the number of results and discarding invalid 3D models that do not match our query. Second, we utilize an approach from computer graphics, the so called ’morphing’, to this application to specialize the models, in order to describe more objects. Third, we search for 3D models using a restricted search space, as obtained from our knowledge of the environment. We show our classification and matching results and finally show how we can recover the correct scaling with the stereo setup of our robot.



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