Abstract
The ability to detect and recognize individuals is essential for an autonomous robot interacting with humans even if computational resources are usually rather limited. In general a small user group can be assumed for interaction. The robot has to distinguish between multiple users and further on between known and unknown persons. For solving this problem we propose an approach which integrates detection, recognition and tracking by formulating all tasks as binary classification problems. Because of its efficiency it is well suited for robots or other systems with limited resources but nevertheless demonstrates robustness and comparable results to state-of-the-art approaches. We use a common over-complete representation which is shared by the different modules. By means of the integral data structure an efficient feature computation is performed enabling the usage of this system for real-time applications such as for our autonomous robot Flea.
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Grabner, M., Grabner, H., Pehserl, J., Korica-Pehserl, P., Bischof, H. (2007). Flea, Do You Remember Me?. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_62
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DOI: https://doi.org/10.1007/978-3-540-76386-4_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76385-7
Online ISBN: 978-3-540-76386-4
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