Elastic Riemannian Framework for Whole-to-Part Shape Registration - Aicha Gatcha; Nadji Hermas; Slami Saadi (International Journal of Computational and Experimental Science and Engineering, 2026)
In this paper, we focus on one of partial shape analysis tasks, by proposing a solution for the whole-to-part shape registration problem using a Riemannian Framework extended from past works. We have a part of a planar curve considered as open one, and the goal is to extract an open curve segment from another closed curve that gives the best alignment by minimizing the Riemannian shape distance between the given part and all parts of the closed curve with the same length. Our contribution here is: (1) extracting all curves with same length of the target curve from the second by changing the starting point, (2) for each part extracted, find the best registration using an elastic Riemannian metric and calculating the shape distance between them (3) the minimum of these distances define the distance desired and the curve is the part which gives this distance. Finally, to evaluate the performance of this algorithm, the results are shown in application to shapes from MPEG-7 dataset.