Abstract
Robust people detection and localization is a prerequisite for many applications where service robots interact with humans. Future robots will not be stand-alone any more but will operate in smart environments that are equipped with sensor systems for context awareness and activity recognition. This paper describes a probabilistic framework for the fusion of data from a laser range finder on a mobile robot and an overhead camera fixed in a domestic environment. The contribution of the framework is that it enables seamless integration with other sensors. For tracking multiple people it is possible to use a probabilistic particle filter tracker. We show that the fusion improves the results of the individual subsystems.
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Hu, N., Englebienne, G., Kröse, B.J.A. (2012). Bayesian Fusion of Ceiling Mounted Camera and Laser Range Finder on a Mobile Robot for People Detection and Localization. In: Salah, A.A., Ruiz-del-Solar, J., Meriçli, Ç., Oudeyer, PY. (eds) Human Behavior Understanding. HBU 2012. Lecture Notes in Computer Science, vol 7559. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34014-7_4
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DOI: https://doi.org/10.1007/978-3-642-34014-7_4
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