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| Author |
Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
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| Title |
Chromatic settings and the structural color constancy index |
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Journal Article |
| Year |
2013 |
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Journal of Vision |
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JV |
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| Volume |
13 |
Issue |
4-3 |
Pages |
1-26 |
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| Abstract |
Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects. |
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CIC; 600.052; 600.051; 605.203 |
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Admin @ si @ RPV2013 |
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2288 |
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| Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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| Title |
Low-level SpatioChromatic Grouping for Saliency Estimation |
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Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
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| Volume |
35 |
Issue |
11 |
Pages |
2810-2816 |
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| Abstract |
We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. |
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0162-8828 |
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CIC; 600.051; 600.052; 605.203 |
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Admin @ si @ MVO2013 |
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2289 |
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| Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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| Title |
Perceptual color texture codebooks for retrieving in highly diverse texture datasets |
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Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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866–869 |
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Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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CIC |
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CAT @ cat @ ASV2010b |
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1426 |
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| Author |
Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras |
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| Title |
Intrinsic Image Evaluation On Synthetic Complex Scenes |
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Conference Article |
| Year |
2013 |
Publication |
20th IEEE International Conference on Image Processing |
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Pages |
285 - 289 |
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| Abstract |
Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth
procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes. |
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Melbourne; Australia; September 2013 |
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CIC; 600.048; 600.052; 600.051 |
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Admin @ si @ BSW2013 |
Serial |
2264 |
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Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras |
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| Title |
The Photometry of Intrinsic Images |
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Conference Article |
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2014 |
Publication |
27th IEEE Conference on Computer Vision and Pattern Recognition |
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1494-1501 |
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Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images. |
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Columbus; Ohio; USA; June 2014 |
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CVPR |
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CIC; 600.052; 600.051; 600.074 |
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no |
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Admin @ si @ SPB2014 |
Serial |
2506 |
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| Author |
A.Gonzalez; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga |
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| Title |
Coloresia: An Interactive Colour Perception Device for the Visually Impaired |
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Book Chapter |
| Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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47-66 |
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A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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CIC; 600.052; 605.203 |
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no |
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Admin @ si @ GBP2013 |
Serial |
2266 |
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| Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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| Title |
3D Texton Spaces for color-texture retrieval |
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Conference Article |
| Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
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6111 |
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354–363 |
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Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel. |
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Springer Berlin Heidelberg |
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A.C. Campilho and M.S. Kamel |
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0302-9743 |
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978-3-642-13771-6 |
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ICIAR |
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CIC |
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no |
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CAT @ cat @ ASV2010a |
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1325 |
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Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
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DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition |
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Conference Article |
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2015 |
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Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II |
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9475 |
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463-473 |
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Projector-camera systems; Feature descriptors; Object recognition |
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Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. |
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Springer International Publishing |
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0302-9743 |
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978-3-319-27862-9 |
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ISVC |
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CIC |
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no |
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Admin @ si @ SMG2015 |
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2736 |
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| Author |
Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva |
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| Title |
Multiresolution colour texture representations for tile classification |
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Miscellaneous |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes |
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ADAS;CIC |
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ADAS @ adas @ LBV1999a |
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3 |
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Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva |
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Visual behaviours for binocular navigation with autonomous systems. |
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Miscellaneous |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes |
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OR;ISE;CIC;MV |
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BCNPCL @ bcnpcl @ RVV1999a |
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13 |
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Maria Vanrell; Jordi Vitria; Xavier Roca |
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A multidimensional scaling approach to explore the behavior of a texture perception algorithm. |
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1997 |
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Machine Vision and Applications |
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262–271 |
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BCNPCL @ bcnpcl @ VVR1997 |
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Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva |
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Gaze control in a binocular robot systems |
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1999 |
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Barcelona |
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OR;ISE;CIC;MV |
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BCNPCL @ bcnpcl @ RVV1999b |
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41 |
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Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva |
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Multiresolution texture classification of ceramic tiles. |
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1999 |
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Recent Research developments in optical engineering, Research Signpost, 2: 213–228 |
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ADAS;CIC |
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ADAS @ adas @ LBV1999b |
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45 |
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Robert Benavente; M.C. Olive; Maria Vanrell; Ramon Baldrich |
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Colour Perception: A Simple Method for Colour Naming. |
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Miscellaneous |
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1999 |
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Girona |
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CAT @ cat @ BOV1999 |
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