ICRA'09 Paper Abstract


Paper FrC3.4

Shin, Jiwon (ETH Zurich), Gachter, Stefan (Swiss Federal Institute of Technology (ETHZ)), Harati, Ahad (ETHZ), Pradalier, Cedric (ETH Zurich), Siegwart, Roland (ETH Zurich)

Object Classification Based on a Geometric Grammar with a Range Camera

Scheduled for presentation during the Regular Sessions "Range Sensing - I" (FrC3), Friday, May 15, 2009, 14:30−14:50, Room: 401

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 21, 2022

Keywords Range Sensing, Computer Vision for Robotics and Automation, Recognition


This paper proposes an object classification framework based on a geometric grammar aimed for mobile robotic applications. The paper first discusses the geometric grammar as a compact representation form for object categories with primitive parts as its constituent elements. The paper then discusses the object classification implemented as parsing of primitive parts. In particular, two approaches are discussed that constrain the search space in order to render the parsing of the primitive parts practical. The two approaches are experimentally verified, first, for a generic object category of chair applied to real range images acquired with a range camera mounted on a mobile robot and, second, for multiple generic object categories applied to synthetic range images. The experimental results show the practicability of the framework.



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