Recognition of generic components using logic-program relations of image contours
Image and Vision Computing
Background Removal in Image Indexing and Retrieval
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
3-D shape approximation using parametric geons
Image and Vision Computing
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The Recognition by Components(RBC) is a theory in Psychology introduced by Biederman in the late 80s, by which humans perceive scenes through simple 3D objects with regular shapes such as spheres, cubes, cylinders, cones, or wedges, called Geons (geometric ions). Extracting geons from 2D images is a very challenging task as it requires a good segmentation and the recognition of the 3D geons in a 2D space. In this paper, we propose a novel approach for extracting 2D geons from 2D images. The process is composed of three major parts: image preprocessing which includes image background removal and segmentation, arc-geon detection, and polygon-geon detection. We also propose a general procedure for matching the extracted 2D geons to given models for object recognition. Experiment results show that our approach is competitive compared to existing object recognition methodologies in general.