Multi-view free-form 3-D object retrieval with incomplete data

This paper describes a novel approach to multi-view 3-D object retrieval. To represent each view of the object, its edge contours are extracted at different levels of scale. Each edge contour, in turn, is segmented by its curvature zero crossing points in a multi-scale fashion. This procedure is carried out using the Curvature Scale Space technique which has been selected for MPEG-7 standardisation. A number of features are then computed for each segment of each edge contour. The image is finally represented by the locations of its segments and the values of their associated features. In response to an input query, geometric hashing is first used to find the best locally matched candidates for the verification stage where the goal is to measure the distance between the input query edge contours and the corresponding model contours after applying a proper transformation. The measurement is then optimised and used as the match value. The method has been successfully tested on a collection of 3-D objects consisting of 15 aircrafts of different shapes.