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Author |
Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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Title |
Generalized Gamut Mapping using Image Derivative Structures for Color Constancy |
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Journal Article |
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Year |
2010 |
Publication |
International Journal of Computer Vision |
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IJCV |
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Volume |
86 |
Issue |
2-3 |
Pages |
127-139 |
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Abstract |
The gamut mapping algorithm is one of the most promising methods to achieve computational color constancy. However, so far, gamut mapping algorithms are restricted to the use of pixel values to estimate the illuminant. Therefore, in this paper, gamut mapping is extended to incorporate the statistical nature of images. It is analytically shown that the proposed gamut mapping framework is able to include any linear filter output. The main focus is on the local n-jet describing the derivative structure of an image. It is shown that derivatives have the advantage over pixel values to be invariant to disturbing effects (i.e. deviations of the diagonal model) such as saturated colors and diffuse light. Further, as the n-jet based gamut mapping has the ability to use more information than pixel values alone, the combination of these algorithms are more stable than the regular gamut mapping algorithm. Different methods of combining are proposed. Based on theoretical and experimental results conducted on large scale data sets of hyperspectral, laboratory and realworld scenes, it can be derived that (1) in case of deviations of the diagonal model, the derivative-based approach outperforms the pixel-based gamut mapping, (2) state-of-the-art algorithms are outperformed by the n-jet based gamut mapping, (3) the combination of the different n-jet based gamut |
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Kluwer Academic Publishers Hingham, MA, USA |
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0920-5691 |
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ISE |
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CAT @ cat @ GGW2010 |
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1274 |
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Author |
Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez |
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Title |
Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences |
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Journal Article |
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Year |
2010 |
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EURASIP Journal on Advances in Signal Processing |
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EURASIPJ |
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Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes. |
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1110-8657 |
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ISE @ ise @ MRR2010 |
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1208 |
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Author |
Marçal Rusiñol; Agnes Borras; Josep Llados |
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Title |
Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images |
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Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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31 |
Issue |
3 |
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188–201 |
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Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings |
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This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results. |
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Elsevier |
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DAG |
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DAG @ dag @ RBL2010 |
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1177 |
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Author |
Marçal Rusiñol; Josep Llados; Gemma Sanchez |
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Title |
Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings |
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Journal Article |
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Year |
2010 |
Publication |
Pattern Analysis and Applications |
Abbreviated Journal |
PAA |
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Volume |
13 |
Issue |
3 |
Pages |
321-331 |
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In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes. |
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Springer-Verlag |
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1433-7541 |
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DAG |
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DAG @ dag @ RLS2010 |
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1165 |
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Author |
Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva |
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Title |
On Tracking Inside Groups |
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Journal Article |
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Year |
2010 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
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Volume |
21 |
Issue |
2 |
Pages |
113–127 |
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Abstract |
This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. |
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Springer-Verlag |
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0932-8092 |
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Call Number |
ISE @ ise @ RGP2010 |
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1158 |
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