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Author |
Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg |
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Title |
Painting-91: A Large Scale Database for Computational Painting Categorization |
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Journal Article |
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Year |
2014 |
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Machine Vision and Applications |
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MVAP |
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25 |
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6 |
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1385-1397 |
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Abstract |
Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms. |
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Springer Berlin Heidelberg |
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0932-8092 |
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CIC; LAMP; 600.074; 600.079 |
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Admin @ si @ KBW2014 |
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2510 |
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Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Parametric Fuzzy Sets for Automatic Color Naming |
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2008 |
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Journal of the Optical Society of America A |
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25 |
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10 |
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2582–2593 |
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CAT @ cat @ BVB2008 |
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1004 |
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Xavier Otazu; Maria Vanrell |
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Perceptual representation of textured images |
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2005 |
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Journal of Imaging Science and Technology, 49(3):262–271 (IF: 0.522) |
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CAT @ cat @ OtV2005b |
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542 |
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C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Title |
Psychophysical measurements to model inter-colour regions of colour-naming space |
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2009 |
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Journal of Imaging Science and Technology |
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53 |
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3 |
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031106 (8 pages) |
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image processing; Analysis |
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JCR Impact Factor 2009: 0.391
In this paper, we present a fuzzy-set of parametric functions which segment the CIE lab space into eleven regions which correspond to the group of common universal categories present in all evolved languages as identified by anthropologists and linguists. The set of functions is intended to model a color-name assignment task by humans and differs from other models in its emphasis on the inter-color boundary regions, which were explicitly measured by means of a psychophysics experiment. In our particular implementation, the CIE lab space was segmented into eleven color categories using a Triple Sigmoid as the fuzzy sets basis, whose parameters are included in this paper. The model’s parameters were adjusted according to the psychophysical results of a yes/no discrimination paradigm where observers had to choose (English) names for isoluminant colors belonging to regions in-between neighboring categories. These colors were presented on a calibrated CRT monitor (14-bit x 3 precision). The experimental results show that inter- color boundary regions are much less defined than expected and color samples other than those near the most representatives are needed to define the position and shape of boundaries between categories. The extended set of model parameters is given as a table. |
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CAT @ cat @ PBV2009 |
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1157 |
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Author |
Daniel Ponsa; Robert Benavente; Felipe Lumbreras; Judit Martinez; Xavier Roca |
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Title |
Quality control of safety belts by machine vision inspection for real-time production |
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2003 |
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Optical Engineering (IF: 0.877) |
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42 |
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4 |
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1114-1120 |
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SPIE |
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ADAS;ISE;CIC |
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ADAS @ adas @ PRL2003 |
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399 |
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