Henrik Andreasson and Tom Duckett
Object Recognition by a Mobile Robot using Omni-directional Vision
Eight Scandinavian Conference on Artificial Intelligence (SCAI), 2003, pp. 3-11
Abstract: This paper proposes a new method for recognizing typical objects found in indoor office environments (tables, chairs, etc.,) by a mobile robot equipped with an omni-directional vision sensor, without requiring any pre-installed geometric models of objects. The approach utilizes the motion of the robot to acquire an internal representation of a given object using ``structure from motion'' or optic flow. First, a set of low-level point features are selected from the segmented area of the image containing the object. The low-level features are tracked by a set of independent Kalman filters as the robot moves through the environment, in order to extract the 3D positions of these points. A set of high-level features is then extracted for input to a pattern recognition system, based on the spatial distribution of the low-level point features. The same feature extraction method is then applied for recognition of the learned objects. Results are presented for some first experiments on a real robot in a laboratory environment.
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Bibtex:
@INPROCEEDINGS{Andreasson_Duckett:SCAI:2003,
  AUTHOR = {Andreasson, Henrik and Duckett, Tom},
  TITLE = {Object Recognition by a Mobile Robot using Omni-directional Vision},
  BOOKTITLE = {Proceedings of the Scandinavian Conference on Artificial Intelligence (SCAI)},
  YEAR = {2003},
  DATE = {November, 2 -- 4},
  ADRESS = {Bergen, Norway},
  PAGES = {3--11}
}