26 September 1997 Object recognition using eigenvectors
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A method for object recognition and pose estimation for robotic bin picking is presented. The approach discussed is a variant on current approaches to eigenimage analysis. Compared to traditional approaches which use object geometry only (shape invariants), the implementation described uses the eigenspace determined by processing the eigenvalues and eigenvectors of the image set. The image set is obtained by varying pose while maintaining a constant level of illumination in space, and the eigenspace is computed for each object of interest. For an unknown input image, the recognition algorithm projects this image to each eigenspace and the object is recognized using space partitioning methods which determine the object and the position in space. Several experimental results have been obtained to demonstrate the robustness of this method when applied to the robotic bin picking task.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ovidiu Ghita, Ovidiu Ghita, Paul F. Whelan, Paul F. Whelan, } "Object recognition using eigenvectors", Proc. SPIE 3208, Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling, (26 September 1997); doi: 10.1117/12.290331; https://doi.org/10.1117/12.290331


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