ICRA 2011 Paper Abstract


Paper WeP104.5

Ikeda, Tetsushi (ATR), Chigodo, Yoshihiro (Osaka University), Miyashita, Takahiro (ATR), Kishino, Fumio (Osaka University), Hagita, Norihiro (ATR)

A Method to Recognize 3D Shapes of Moving Targets Based on Integration of Inclined 2D Range Scans

Scheduled for presentation during the Regular Sessions "Range Sensing III" (WeP104), Wednesday, May 11, 2011, 14:40−14:55, Room 3E

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on July 14, 2020

Keywords Range Sensing, Recognition, Surveillance Systems


Recently, laser-based people-tracking systems have received increasing attention for their ability to localize human subjects precisely in crowded situations. However, in a real environment, there exist many kinds of moving objects other than people, and previous methods have focused only on humans. To design a more sophisticated system, it is necessary to distinguish humans from observed objects and recognize their individual condition—for example, the kind and amount of belongings they are carrying. However, in previous methods using 2D laser range finders (LRFs), it proved difficult to recognize the type of target since all sensors observe a common horizontal plane and only the 2D contours of their targets. In this study, to recognize the type of target, we observe the 3D shapes of objects moving in their environment by installing LRFs with an angle of inclination. So far, in the area of 3D modeling, LRFs have been used to construct 3D models of static objects by moving the sensor and registering multiple views. In contrast, our method observes moving objects by using a static LRF network in the environment. Experimental results are shown to confirm the effectiveness of the proposed method.



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