Non-Rigid Puzzles
This work is significant for computer graphics and vision researchers working on shape correspondence, particularly in challenging scenarios with non-rigid deformations and partial data, offering a robust solution for a complex matching problem.
This paper addresses the problem of matching multiple non-rigidly deformed and partially observed 3D shape parts to a reference shape. The method simultaneously segments the reference model and establishes dense correspondence to the query parts, even with clutter, overlap, and missing/redundant parts.
Shape correspondence is a fundamental problem in computer graphics and vision, with applications in various problems including animation, texture mapping, robotic vision, medical imaging, archaeology and many more. In settings where the shapes are allowed to undergo non-rigid deformations and only partial views are available, the problem becomes very challenging. To this end, we present a non-rigid multi-part shape matching algorithm. We assume to be given a reference shape and its multiple parts undergoing a non-rigid deformation. Each of these query parts can be additionally contaminated by clutter, may overlap with other parts, and there might be missing parts or redundant ones. Our method simultaneously solves for the segmentation of the reference model, and for a dense correspondence to (subsets of) the parts. Experimental results on synthetic as well as real scans demonstrate the effectiveness of our method in dealing with this challenging matching scenario.