Abstract. Human perception of shape is based on visual parts of objects to a point that a single, significant visual part is sufficient to recognize the whole object. For example, if you see a hand in the door, you expect a human behind the door. Therefore, a cognitively motivated shape similarity measure for recognition applications should be based on visual parts. This cognitive assumption leads to two related problems of scale selection and subpart selection. To find a given query part Q as part of an object C, Q needs to have a correct size with regards to C (scale selection). Assuming that the correct size is selected, the part Q must be compared to all possible subparts of C (subpart selection). For global, contour-based similarity measures, scaling the whole contour curves of both objects to the same length usually solves the problem of scale selection. Although this is not an optimal solution, it works if the whole contour curves are 'sufficiently' similar. Subpart selection problem does not occur in the implementation of global similarity measures. In this paper we present a shape similarity system that is based on correspondence of visual parts, and apply it to robot localization and mapping. This is a particularly interesting application, since the scale selection problem does not occur here and visual parts can be obtained in a very simple way. Therefore, only the problem of subpart selection needs to be solved. Our solution to this problem is based on a contour based shape similarity measure supplemented by a structural arrangement information of visual parts. Shape descriptors for comparing silhouettes of 2D objects in order to determine their similarity are important and useful for wide range of applications, of which the most obvious is shape-based object retrieval in image databases. Shape's importance is indicated by the fact that the MPEG-7 group incorporated shape descriptors into the MPEG-7 standard. Since the 2D objects are projections of 3D objects their silhouettes may change due to: 1. change of a view point with respect to objects,
Applicability of the elementary shape similarity measure has been shown in REF .
Shape Similarity and Visual Parts
DGCI
Computer Science