Detail-Preserving Mesh Unfolding for Nonrigid Shape Retrieval

We present a shape deformation algorithm that unfolds any given 3D shape into a canonical pose that is invariant to nonrigid transformations. Unlike classical approaches, such as least-squares multidimensional scaling, we preserve the geometric details of the input shape in the resulting shape, which in turn leads to a content-based nonrigid shape retrieval application with higher accuracy. Our optimization framework, fed with a triangular or a tetrahedral mesh in 3D, tries to move each vertex as far away from each other as possible subject to finite element regularization constraints. Intuitively this effort minimizes the bending over the shape while preserving the details. Avoiding geodesic distances in our computation renders the method robust to topological noise. Compared to state-of-the-art approaches, our method is simpler to implement, faster, more accurate in shape retrieval, and less sensitive to topological errors.


3B Izometrik Şekil Eşleme
Sahillioğlu, Yusuf (2010-06-01)
3B izometrik şekiller arasındaki eşleme problemini ele alıyoruz. Önerdiğimiz yöntem, verilen iki izometrik şekil arasındaki izometrik sapmayı enküçülten optimal eşlemeyi otomatik olarak bulabilmektedir.İzometri hatasını iki adımda eniyiliyoruz. İlk adımda, şekil yüzeylerinden örneklenmiş bir örnek 3B noktalar kesel ilginlik bilgisine dayanarak spektral uzaya aktarılır.İlk eşleme spektral uzayda tam iki kısımlı bir çizge eşleştirme yöntemi kullanarak izometri hatasının polinom zamanda enküçültülmesiyle eld...
3D Correspondence by Breadth First Search Frontiers
Sahillioğlu, Yusuf (null; 2009-06-01)
This paper presents a novel, robust, and fast 3D shape correspondence algorithm applicable to the two snapshots of the same object in arbitrary deformation. Given two such frames as triangle meshes with fixed connectivity, our algorithm first classifies vertices into Breadth-First Search (BFS) frontiers according to their unweighted shortest path distance from a source vertex. This is followed by the rigid or non-rigid alignment of the corresponding frontiers of two meshes as the second and final step. This...
Part-based data-driven 3D shape interpolation
Aydinlilar, Melike; Sahillioğlu, Yusuf (2021-07-01)
An active problem in digital geometry processing is shape interpolation which aims to generate a continuous sequence of in-betweens for a given source and target shape. Unlike traditional approaches that interpolate source and target shapes in isolation, recent data-driven approaches utilize multiple interpolations through intermediate database shapes, and consequently perform better at the expense of a database requirement. In contrast to the existing data-driven approaches that consider intermediate shape...
3D object representation using transform and scale invariant 3D features
AKAGÜNDÜZ, Erdem; Ulusoy, İlkay (2007-10-21)
An algorithm is proposed for 3D object representation using generic 3D features which are transformation and scale invariant. Descriptive 3D features and their relations are used to construct a graphical model for the object which is later trained and then used for detection purposes. Descriptive 3D features are the fundamental structures which are extracted from the surface of the 3D scanner output. This surface is described by mean and Gaussian curvature values at every data point at various scales and a ...
Coarse-to-Fine Isometric Shape Correspondence by Tracking Symmetric Flips
Sahillioğlu, Yusuf; Yemez, Y. (2013-02-01)
We address the symmetric flip problem that is inherent to multi-resolution isometric shape matching algorithms. To this effect, we extend our previous work which handles the dense isometric correspondence problem in the original 3D Euclidean space via coarse-to-fine combinatorial matching. The key idea is based on keeping track of all optimal solutions, which may be more than one due to symmetry especially at coarse levels, throughout denser levels of the shape matching process. We compare the resulting den...
Citation Formats
Y. Sahillioğlu, “Detail-Preserving Mesh Unfolding for Nonrigid Shape Retrieval,” ACM TRANSACTIONS ON GRAPHICS, pp. 0–0, 2016, Accessed: 00, 2020. [Online]. Available: