Evaluation of approaches combining 2D and 3D data for object recognition developed for the mobile robot Lisa

Viktor Seib; Florian Polster; Dietrich Paulus

doi:10.1117/12.2266256

8 February 2017 Evaluation of approaches combining 2D and 3D data for object recognition developed for the mobile robot Lisa

Viktor Seib, Florian Polster, Dietrich Paulus

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Proceedings Volume 10253, 2016 International Conference on Robotics and Machine Vision; 102530F (2017) https://doi.org/10.1117/12.2266256
Event: 2016 International Conference on Robotics and Machine Vision, 2016, Moscow, Russia

Abstract

The image data that object recognition systems are designed for changes over time. As soon as a new imaging technology is developed or becomes affordable new algorithms are inspired or known algorithms are adapted. Thus, different object recognition algorithms were developed and used on our mobile robot Lisa. In this work we compare the different approaches and investigate how they can be combined to best use 2D and 3D data. The individual approaches as well as their combinations will be introduced. Evaluation is performed on a large public dataset and a dataset acquired during the RoboCup competition.

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Viktor Seib, Florian Polster, and Dietrich Paulus "Evaluation of approaches combining 2D and 3D data for object recognition developed for the mobile robot Lisa", Proc. SPIE 10253, 2016 International Conference on Robotics and Machine Vision, 102530F (8 February 2017); https://doi.org/10.1117/12.2266256

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KEYWORDS

Object recognition

Detection and tracking algorithms

Algorithm development

Mobile robots

Feature extraction

RGB color model

3D modeling

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