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Author |
Shida Beigpour; Christian Riess; Joost Van de Weijer; Elli Angelopoulou |
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Title |
Multi-Illuminant Estimation with Conditional Random Fields |
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Journal Article |
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2014 |
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IEEE Transactions on Image Processing |
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TIP |
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23 |
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1 |
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83-95 |
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Keywords |
color constancy; CRF; multi-illuminant |
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Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach. |
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1057-7149 |
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CIC; LAMP; 600.074; 600.079 |
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Admin @ si @ BRW2014 |
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2451 |
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Author |
Carlo Gatta; Francesco Ciompi |
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Title |
Stacked Sequential Scale-Space Taylor Context |
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Journal Article |
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2014 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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36 |
Issue |
8 |
Pages |
1694-1700 |
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We analyze sequential image labeling methods that sample the posterior label field in order to gather contextual information. We propose an effective method that extracts local Taylor coefficients from the posterior at different scales. Results show that our proposal outperforms state-of-the-art methods on MSRC-21, CAMVID, eTRIMS8 and KAIST2 data sets. |
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0162-8828 |
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LAMP; MILAB; 601.160; 600.079 |
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Admin @ si @ GaC2014 |
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2466 |
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Author |
Pedro Martins; Paulo Carvalho; Carlo Gatta |
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Title |
Context-aware features and robust image representations |
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2014 |
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Journal of Visual Communication and Image Representation |
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JVCIR |
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25 |
Issue |
2 |
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339-348 |
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Local image features are often used to efficiently represent image content. The limited number of types of features that a local feature extractor responds to might be insufficient to provide a robust image representation. To overcome this limitation, we propose a context-aware feature extraction formulated under an information theoretic framework. The algorithm does not respond to a specific type of features; the idea is to retrieve complementary features which are relevant within the image context. We empirically validate the method by investigating the repeatability, the completeness, and the complementarity of context-aware features on standard benchmarks. In a comparison with strictly local features, we show that our context-aware features produce more robust image representations. Furthermore, we study the complementarity between strictly local features and context-aware ones to produce an even more robust representation. |
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LAMP; 600.079;MILAB |
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Admin @ si @ MCG2014 |
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2467 |
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Simeon Petkov; Xavier Carrillo; Petia Radeva; Carlo Gatta |
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Diaphragm border detection in coronary X-ray angiographies: New method and applications |
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2014 |
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Computerized Medical Imaging and Graphics |
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CMIG |
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38 |
Issue |
4 |
Pages |
296-305 |
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X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation. |
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MILAB; LAMP; 600.079 |
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Admin @ si @ PCR2014 |
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2468 |
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Author |
Francesco Ciompi; Oriol Pujol; Petia Radeva |
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Title |
ECOC-DRF: Discriminative random fields based on error correcting output codes |
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Journal Article |
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Year |
2014 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
47 |
Issue |
6 |
Pages |
2193-2204 |
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Keywords |
Discriminative random fields; Error-correcting output codes; Multi-class classification; Graphical models |
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We present ECOC-DRF, a framework where potential functions for Discriminative Random Fields are formulated as an ensemble of classifiers. We introduce the label trick, a technique to express transitions in the pairwise potential as meta-classes. This allows to independently learn any possible transition between labels without assuming any pre-defined model. The Error Correcting Output Codes matrix is used as ensemble framework for the combination of margin classifiers. We apply ECOC-DRF to a large set of classification problems, covering synthetic, natural and medical images for binary and multi-class cases, outperforming state-of-the art in almost all the experiments. |
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LAMP; HuPBA; MILAB; 605.203; 600.046; 601.043; 600.079 |
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Call Number |
Admin @ si @ CPR2014b |
Serial |
2470 |
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