Athanasios Mademlis

3D object retrieval using the 3D shape impact descriptor

In this paper, the novel 3D shape impact descriptor is introduced, which is based on the resulting gravitational phenomena in the surrounding area of every 3D object. The 3D object is considered as a distributed 3D mass and the descriptor of the 3D object is indirectly computed from the resulting fields. The field is described using both Newtons and general relativitys laws. In the Newtonian approach, histograms of the field values in the surrounding area of the 3D object are computed, while in the relativistic approach the descriptors are histograms of the time-space curvature in the surrounding area of the 3D object. The basic motivation behind the proposed approach is the robustness with respect to objects degeneracies and the native invariance of the resulting descriptors under rotation and translation. Experiments which were performed in various 3D object databases proved that the proposed method can be efficiently used for 3D object retrieval applications.

Combining Topological and Geometrical Features for Global and Partial 3-D Shape Retrieval

This paper presents a novel framework for 3-D object content-based search and retrieval, appropriate for both partial and global matching applications. The framework is based on a graph representation of a 3-D object which is enhanced by local geometric features. The 3-D object is decomposed into meaningful parts and an attributed graph is constructed based on the connectivity of the parts. Every 3-D part is approximated with a suitable superellipsoid and a novel 3-D shape descriptor, called a 3-D distance field descriptor, is computed and associated to the corresponding graph nodes. The matching process used is based on attributed graph matching algorithm appropriate for this application. The proposed method not only provides successful retrieval results in terms of geometric similarity but also is invariant to rotation, translation and scaling of an object as well as to the different poses of articulated objects. Finally, it can be effectively used for partial and global 3-D object retrieval.

3D Content-Based Search Based on 3D Krawtchouk Moments

In this paper a novel method for 3D content-based search and retrieval is proposed. Guided by the imperative need for a reliable 3D content based search tool and the very interesting results of research work done in the past on the performance of Krawtchouk moments and Krawtchouk moment invariants in image processing, Weighted 3D Krawtchouk moments are introduced for efficient 3D analysis which are suitable for content-based search and retrieval applications. The proposed method was tested on Princeton Shape Benchmark. Experiments have shown that the proposed method is superior in terms of precision-recall comparing with other well-known methods reported in the literature.

Blind Robust 3-D Mesh Watermarking Based on Oblate Spheroidal Harmonics

In this paper, a novel transform-based, blind and robust 3-D mesh watermarking scheme is presented. The 3-D surface of the mesh is firstly divided into a number of discrete continuous regions, each of which is successively sampled and mapped onto oblate spheroids, using a novel surface parameterization scheme. The embedding is performed in the spheroidal harmonic coefficients of the spheroids, using a novel embedding scheme. Changes made to the transform domain are then reversed back to the spatial domain, thus forming the watermarked 3-D mesh. The embedding scheme presented herein resembles, in principal, the ones using the multiplicative embedding rule (inherently providing high imperceptibility). The watermark detection is blind and by far more powerful than the various correlators typically incorporated by multiplicative schemes. Experimental results have shown that the proposed blind watermarking scheme is competitively robust against similarity transformations, connectivity attacks, mesh simplification and refinement, unbalanced resampling, smoothing and noise addition, even when juxtaposed to the informed ones.

SHREC'09 track: structural shape retrieval on watertight models

The annual SHape REtrieval Contest (SHREC) measures the performance of 3D model retrieval methods for several different types of models and retrieval purposes. In this contest the structural shape retrieval track focuses on the retrieval of 3d models which exhibit a relevant similarity in the shape structure. Shape structure is typically characterised by features like protrusions, holes and concavities. It defines relationships in which components of the shape are connected.

Ellipsoidal Harmonics for 3-D Shape Description and Retrieval

In this paper, a novel approach for 3-D Shape description and retrieval based on the theory of ellipsoidal harmonics is presented. Four novel descriptors are introduced: the surface ellipsoidal harmonics descriptor, which concerns 3-D objects that are described as polygonal surfaces; the volumetric ellipsoidal harmonics descriptor, which is applicable to volumetric 3-D objects; the generalized ellipsoidal harmonics descriptor that is applied to any local 3-D object descriptors; and, finally, the combined ellipsoidal-spherical harmonics descriptor, which leads to a compact and powerful descriptor that inherits the advantages of both approaches: the rotation invariance properties of the spherical harmonics and the directional information enclosed in ellipsoidal harmonics. Experimental results performed using well-known 3-D object databases prove the retrieval efficiency of the proposed approach.

On 3D Partial Matching of Meaningful Parts

In this paper, a method suitable for partial matching between 3D objects is presented. The 3D objects are firstly segmented into meaningful parts extending a method which is based on the medial surface of the objects. Then, geometric features are extracted for each part using the spherical trace transform. The extracted features are combined and their covariance matrix is computed as a descriptor of each part. The contribution of the proposed approach is that a meaningful segmentation of 3D objects based on medial surface is achieved and that partial matching is performed on meaningful parts, in a rotation, translation and scaling invariant manner. The experimental results performed, proved that the proposed approach achieves accurate partial matching results in terms of distinct meaningful parts as well as satisfactory overall accuracy.

I-SEARCH: a multimodal search engine based on rich unified content description (RUCoD)

In this paper, we report on work around the I-SEARCH EU (FP7 ICT STREP) project whose objective is the development of a multimodal search engine. We present the projects objectives, and detail the achieved results, amongst which a Rich Unified Content Description format.

A Novel Prototype for Documentation and Retrieval of 3D Objects

In this paper a working multimedia asset management system is presented which provides the means for storage, annotation, retrieval and re-use of any multimedia data such as 3D objects, images, sound, video and text. The working prototype is modular, customizable, secure, offers intranet and Internet connectivity and also software inter-operability as it can be compatible with various well- known, established database and ontology standards. The main innovative aspects of the proposed system are the efficient combination of the semantic aspects with multimedia data and the retrieval engine of the system which combines state-of-the-art 3D content-based algorithms and novel semantic driven, relevance feedback methods.

A map-search framework based on attributed graph matching

Our proposed sketch-based search and retrieval system in map databases shows the promise that intuitive search can be possible even when searching in nonannotated conventional map data. We plan to perform further work in this area to allow for more intuitive and semantic queries, applications for mobile and ubiquitous computing, and integration to existing map searching applications.