This work is concerned with a framework for visual object recognition in real world tasks. Our approach is motivated by biological findings of the representation of space around the body, the so-called peripersonal space. We show that the principles behind those findings can lead to a natural structuring of object recognition tasks in artificial systems. We demonstrate this by the supervised learning and recognition of 20 complex-shaped objects from unsegmented visual input. © 2005 IEEE.
CITATION STYLE
Goerick, C., Wersing, H., Mikhailova, I., & Dunn, M. (2005). Peripersonal space and object recognition for humanoids. In Proceedings of 2005 5th IEEE-RAS International Conference on Humanoid Robots (Vol. 2005, pp. 387–392). https://doi.org/10.1109/ICHR.2005.1573598
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