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Fast Image Classification for Monument Recognition
Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro
Article No.: 18
Content-based image classification is a wide research field that addresses the landmark recognition problem. Among the many classification techniques proposed, the k-nearest neighbor (kNN) is one of the most simple and widely used...
3D Artifacts Similarity Based on the Concurrent Evaluation of Heterogeneous Properties
Silvia Biasotti, Andrea Cerri, Bianca Falcidieno, Michela Spagnuolo
Article No.: 19
Archaeological artifacts are often classified in homogeneous groups, according to either intangible properties (e.g., origin, use, age) or physical features (e.g., color, material, geometric shape, size, style). In particular, a single property is...
Folk Dance Evaluation Using Laban Movement Analysis
Andreas Aristidou, Efstathios Stavrakis, Panayiotis Charalambous, Yiorgos Chrysanthou, Stephania Loizidou Himona
Article No.: 20
Motion capture (mocap) technology is an efficient method for digitizing art performances, and is becoming increasingly popular in the preservation and dissemination of dance performances. Although technically the captured data can be of very high...
The ROV 3D Project: Deep-Sea Underwater Survey Using Photogrammetry: Applications for Underwater Archaeology
Pierre Drap, Julien Seinturier, Bilal Hijazi, Djamal Merad, Jean-Marc Boi, Bertrand Chemisky, Emmanuelle Seguin, Luc Long
Article No.: 21
In this article, we present an approach for a deep-sea survey based on photogrammetry using a remotely operated underwater vehicle (ROV). A hybrid technique gives us real-time results, sufficient for piloting the ROV from the surface vessel and...
Adaptive Sparse Representation for Analyzing Artistic Style of Paintings
Zhi Gao, Mo Shan, Qingquan Li
Article No.: 22
Inspired by the outstanding performance of sparse representation (SR) in a variety of image/video relevant classification and identification tasks, we propose an adaptive SR method for painting style analysis. Significantly improved over previous...