Apostolos Axenopoulos

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This paper presents a unified framework for 3D shape retrieval. The method supports multimodal queries (2D images, sketches, 3D objects) by introducing a novel view-based approach able to handle the different types of multimedia data. More specifically, a set of 2D images (multi-views) are automatically generated from a 3D object, by taking views from(More)
The objective of the Shape Retrieval Contest ’09 (SHREC’09) of Partial Models is to compare the performances of algorithms that accept a range image as the query and retrieve relevant 3D models from a database. The use of a range scan of an object as the query addresses real life scenarios, where the task of the system is to analyze a 3D scene and to(More)
In this paper we present the results of the SHREC’09Generic Shape Retrieval Contest. The aim of this track was to evaluate the performances of various 3D shape retrieval algorithms on the NIST generic shape benchmark. We hope that the NIST shape benchmark will provide valuable contributions to the 3D shape retrieval community. Seven groups have participated(More)
In this paper, a 3D shape-based approach is presented for the efficient search, retrieval, and classification of protein molecules. The method relies primarily on the geometric 3D structure of the proteins, which is produced from the corresponding PDB files and secondarily on their primary and secondary structure. After proper positioning of the 3D(More)
This paper presents the results of the SHREC’10 Protein Models Classification Track. The aim of this track is to evaluate how well 3D shape recognition algorithms can classify protein structures according to the CATH [CSL08] superfamily classification. Five groups participated in this track, using a total of six methods, and for each method a set of ranked(More)
This paper proposes a novel framework for 3-D object retrieval, taking into account most of the factors that may affect the retrieval performance. Initially, a novel 3-D model alignment method is introduced, which achieves accurate rotation estimation through the combination of two intuitive criteria, plane reflection symmetry and rectilinearity. After the(More)
In this paper, a real-time tracking-based approach to human action recognition is proposed. The method receives as input depth map data streams from a single kinect sensor. Initially, a skeleton-tracking algorithm is applied. Then, a new action representation is introduced, which is based on the calculation of spherical angles between selected joints and(More)