Abstract
The approach presented shows possible ways of improving scene analysis to achieve more reliable and accurate object recognition in the context of mobile robotics. The centralized architecture combines different feature detectors with active modalities, such as change of perspective or influencing the scene. It opens possibilities for the use of 2D detectors and extends the results to 3D. In combination with mixed reality, it offers the possibility of evaluation of the developed system as well as increased efficiency. The architecture developed and the preliminary results are presented. The work goes a step in the direction of active intelligent perception.
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Acknowledgments
The authors would like to thank William Morris for his structural feedback and Robert Wieczoreck for supporting the implementation of the calibration procedure. This work has been conducted as part of RACE, funded under the European Community’s Seventh Framework Programme FP7-ICT-2011-7 under grant agreement n 287752 (http://www.project-race.eu/).
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Klimentjew, D., Rockel, S., Zhang, J. (2014). Active Scene Analysis Based on Multi-Sensor Fusion and Mixed Reality on Mobile Systems. In: Sun, F., Hu, D., Liu, H. (eds) Foundations and Practical Applications of Cognitive Systems and Information Processing. Advances in Intelligent Systems and Computing, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37835-5_69
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DOI: https://doi.org/10.1007/978-3-642-37835-5_69
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