Qualitative part-based models in content-based image retrieval
Machine Vision and Applications
Detection of unexpected multi-part objects from segmented contour maps
Pattern Recognition
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In this paper, a top-down approach based on perceptual grouping is proposed for multi-part objects detection. The abstract conceptual category of multi-part objects is formalized by a set of global criteria. These criteria will enable the evaluation of the segmentation quality in order to determine if the whole grouping is perceptually significant and if it has a good perceptual shape. A new cognitive vision methodology, called SAFE (Subjectivity And Formalism Explicitly), is presented. Its goal is to help identify the proper global criteria and to validate the judgment derived from formal calculations of these criteria by human judgment.