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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 | Type | Journal Article | |||
| Year | 2013 | Publication | Journal of Vision | Abbreviated Journal | JV | |
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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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| Notes | CIC; 600.052; 600.051; 605.203 | Approved | no | |||
| Call Number | Admin @ si @ RPV2013 | Serial | 2288 | |||
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| Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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| Title | Computational Color Constancy: Survey and Experiments | Type | Journal Article | |||
| Year | 2011 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
| Volume |
20 | Issue | 9 | Pages | 2475-2489 | |
| Keywords | computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting | |||||
| Abstract | Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets. | |||||
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| ISSN | 1057-7149 | ISBN | Medium | |||
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| Notes | ISE;CIC | Approved | no | |||
| Call Number | Admin @ si @ GGW2011 | Serial | 1717 | |||
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| Author | Javier Vazquez; Maria Vanrell; Ramon Baldrich; Francesc Tous |
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| Title | Color Constancy by Category Correlation | Type | Journal Article | |||
| Year | 2012 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
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21 | Issue | 4 | Pages | 1997-2007 | |
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| Abstract | Finding color representations which are stable to illuminant changes is still an open problem in computer vision. Until now most approaches have been based on physical constraints or statistical assumptions derived from the scene, while very little attention has been paid to the effects that selected illuminants have
on the final color image representation. The novelty of this work is to propose perceptual constraints that are computed on the corrected images. We define the category hypothesis, which weights the set of feasible illuminants according to their ability to map the corrected image onto specific colors. Here we choose these colors as the universal color categories related to basic linguistic terms which have been psychophysically measured. These color categories encode natural color statistics, and their relevance across different cultures is indicated by the fact that they have received a common color name. From this category hypothesis we propose a fast implementation that allows the sampling of a large set of illuminants. Experiments prove that our method rivals current state-of-art performance without the need for training algorithmic parameters. Additionally, the method can be used as a framework to insert top-down information from other sources, thus opening further research directions in solving for color constancy. |
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| ISSN | 1057-7149 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VVB2012 | Serial | 1999 | |||
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| Author | Trevor Canham; Javier Vazquez; Elise Mathieu; Marcelo Bertalmío |
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| Title | Matching visual induction effects on screens of different size | Type | Journal Article | |||
| Year | 2021 | Publication | Journal of Vision | Abbreviated Journal | JOV | |
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21 | Issue | 6(10) | Pages | 1-22 | |
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| Abstract | In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen–size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images. | |||||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ CVM2021 | Serial | 3595 | |||
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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 | Type | Journal Article | |||
| Year | 2014 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
| Volume |
23 | Issue | 1 | Pages | 83-95 | |
| Keywords | color constancy; CRF; multi-illuminant | |||||
| Abstract | 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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| ISSN | 1057-7149 | ISBN | Medium | |||
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| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ BRW2014 | Serial | 2451 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Muhammad Anwer Rao; Michael Felsberg; Carlo Gatta |
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| Title | Semantic Pyramids for Gender and Action Recognition | Type | Journal Article | |||
| Year | 2014 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
| Volume |
23 | Issue | 8 | Pages | 3633-3645 | |
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| Abstract | Person description is a challenging problem in computer vision. We investigated two major aspects of person description: 1) gender and 2) action recognition in still images. Most state-of-the-art approaches for gender and action recognition rely on the description of a single body part, such as face or full-body. However, relying on a single body part is suboptimal due to significant variations in scale, viewpoint, and pose in real-world images. This paper proposes a semantic pyramid approach for pose normalization. Our approach is fully automatic and based on combining information from full-body, upper-body, and face regions for gender and action recognition in still images. The proposed approach does not require any annotations for upper-body and face of a person. Instead, we rely on pretrained state-of-the-art upper-body and face detectors to automatically extract semantic information of a person. Given multiple bounding boxes from each body part detector, we then propose a simple method to select the best candidate bounding box, which is used for feature extraction. Finally, the extracted features from the full-body, upper-body, and face regions are combined into a single representation for classification. To validate the proposed approach for gender recognition, experiments are performed on three large data sets namely: 1) human attribute; 2) head-shoulder; and 3) proxemics. For action recognition, we perform experiments on four data sets most used for benchmarking action recognition in still images: 1) Sports; 2) Willow; 3) PASCAL VOC 2010; and 4) Stanford-40. Our experiments clearly demonstrate that the proposed approach, despite its simplicity, outperforms state-of-the-art methods for gender and action recognition. | |||||
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| ISSN | 1057-7149 | ISBN | Medium | |||
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| Notes | CIC; LAMP; 601.160; 600.074; 600.079;MILAB | Approved | no | |||
| Call Number | Admin @ si @ KWR2014 | Serial | 2507 | |||
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| Author | Jaykishan Patel; Alban Flachot; Javier Vazquez; David H. Brainard; Thomas S. A. Wallis; Marcus A. Brubaker; Richard F. Murray |
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| Title | A deep convolutional neural network trained to infer surface reflectance is deceived by mid-level lightness illusions | Type | Journal Article | |||
| Year | 2023 | Publication | Journal of Vision | Abbreviated Journal | JV | |
| Volume |
23 | Issue | 9 | Pages | 4817-4817 | |
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| Abstract | A long-standing view is that lightness illusions are by-products of strategies employed by the visual system to stabilize its perceptual representation of surface reflectance against changes in illumination. Computationally, one such strategy is to infer reflectance from the retinal image, and to base the lightness percept on this inference. CNNs trained to infer reflectance from images have proven successful at solving this problem under limited conditions. To evaluate whether these CNNs provide suitable starting points for computational models of human lightness perception, we tested a state-of-the-art CNN on several lightness illusions, and compared its behaviour to prior measurements of human performance. We trained a CNN (Yu & Smith, 2019) to infer reflectance from luminance images. The network had a 30-layer hourglass architecture with skip connections. We trained the network via supervised learning on 100K images, rendered in Blender, each showing randomly placed geometric objects (surfaces, cubes, tori, etc.), with random Lambertian reflectance patterns (solid, Voronoi, or low-pass noise), under randomized point+ambient lighting. The renderer also provided the ground-truth reflectance images required for training. After training, we applied the network to several visual illusions. These included the argyle, Koffka-Adelson, snake, White’s, checkerboard assimilation, and simultaneous contrast illusions, along with their controls where appropriate. The CNN correctly predicted larger illusions in the argyle, Koffka-Adelson, and snake images than in their controls. It also correctly predicted an assimilation effect in White's illusion. It did not, however, account for the checkerboard assimilation or simultaneous contrast effects. These results are consistent with the view that at least some lightness phenomena are by-products of a rational approach to inferring stable representations of physical properties from intrinsically ambiguous retinal images. Furthermore, they suggest that CNN models may be a promising starting point for new models of human lightness perception. | |||||
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| Notes | MACO; CIC | Approved | no | |||
| Call Number | Admin @ si @ PFV2023 | Serial | 3890 | |||
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| Author | Robert Benavente; Maria Vanrell; Ramon Baldrich |
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| Title | Parametric Fuzzy Sets for Automatic Color Naming | Type | Journal | |||
| Year | 2008 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | ||
| Volume |
25 | Issue | 10 | Pages | 2582–2593 | |
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ BVB2008 | Serial | 1004 | |||
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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 | Type | Journal Article | |||
| Year | 2014 | Publication | Machine Vision and Applications | Abbreviated Journal | MVAP | |
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25 | Issue | 6 | Pages | 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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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | |||
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| ISSN | 0932-8092 | ISBN | Medium | |||
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| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ KBW2014 | Serial | 2510 | |||
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| Author | Xavier Otazu; Oriol Pujol |
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| Title | Wavelet based approach to cluster analysis. Application on low dimensional data sets | Type | Journal Article | |||
| Year | 2006 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL | |
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27 | Issue | 14 | Pages | 1590–1605 | |
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| Notes | MILAB; CIC; HuPBA | Approved | no | |||
| Call Number | BCNPCL @ bcnpcl @ OtP2006 | Serial | 658 | |||
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| Author | Eduard Vazquez; Theo Gevers; M. Lucassen; Joost Van de Weijer; Ramon Baldrich |
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| Title | Saliency of Color Image Derivatives: A Comparison between Computational Models and Human Perception | Type | Journal Article | |||
| Year | 2010 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A | |
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27 | Issue | 3 | Pages | 613–621 | |
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| Abstract | In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%. | |||||
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| Notes | ISE;CIC | Approved | no | |||
| Call Number | CAT @ cat @ VGL2010 | Serial | 1275 | |||
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| Author | Graham D. Finlayson; Javier Vazquez; Sabine Süsstrunk; Maria Vanrell |
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| Title | Spectral sharpening by spherical sampling | Type | Journal Article | |||
| Year | 2012 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A | |
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29 | Issue | 7 | Pages | 1199-1210 | |
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| Abstract | There are many works in color that assume illumination change can be modeled by multiplying sensor responses by individual scaling factors. The early research in this area is sometimes grouped under the heading “von Kries adaptation”: the scaling factors are applied to the cone responses. In more recent studies, both in psychophysics and in computational analysis, it has been proposed that scaling factors should be applied to linear combinations of the cones that have narrower support: they should be applied to the so-called “sharp sensors.” In this paper, we generalize the computational approach to spectral sharpening in three important ways. First, we introduce spherical sampling as a tool that allows us to enumerate in a principled way all linear combinations of the cones. This allows us to, second, find the optimal sharp sensors that minimize a variety of error measures including CIE Delta E (previous work on spectral sharpening minimized RMS) and color ratio stability. Lastly, we extend the spherical sampling paradigm to the multispectral case. Here the objective is to model the interaction of light and surface in terms of color signal spectra. Spherical sampling is shown to improve on the state of the art. | |||||
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| ISSN | 1084-7529 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ FVS2012 | Serial | 2000 | |||
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| Author | Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell |
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| Title | Describing Reflectances for Colour Segmentation Robust to Shadows, Highlights and Textures | Type | Journal Article | |||
| Year | 2011 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI | |
| Volume |
33 | Issue | 5 | Pages | 917-930 | |
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| Abstract | The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost. | |||||
| Address | Los Alamitos; CA; USA; | |||||
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| Publisher | IEEE Computer Society | Place of Publication | Editor | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 0162-8828 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VBW2011 | Serial | 1715 | |||
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| Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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| Title | Improving Color Constancy by Photometric Edge Weighting | Type | Journal Article | |||
| Year | 2012 | Publication | IEEE Transaction on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI | |
| Volume |
34 | Issue | 5 | Pages | 918-929 | |
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| Abstract | : Edge-based color constancy methods make use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as material, shadow and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation. Therefore, in this paper, an extensive analysis is provided of different edge types on the performance of edge-based color constancy methods. First, an edge-based taxonomy is presented classifying edge types based on their photometric properties (e.g. material, shadow-geometry and highlights). Then, a performance evaluation of edge-based color constancy is provided using these different edge types. From this performance evaluation it is derived that specular and shadow edge types are more valuable than material edges for the estimation of the illuminant. To this end, the (iterative) weighted Grey-Edge algorithm is proposed in which these edge types are more emphasized for the estimation of the illuminant. Images that are recorded under controlled circumstances demonstrate that the proposed iterative weighted Grey-Edge algorithm based on highlights reduces the median angular error with approximately $25\%$. In an uncontrolled environment, improvements in angular error up to $11\%$ are obtained with respect to regular edge-based color constancy. | |||||
| Address | Los Alamitos; CA; USA; | |||||
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| ISSN | 0162-8828 | ISBN | Medium | |||
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| Notes | CIC;ISE | Approved | no | |||
| Call Number | Admin @ si @ GGW2012 | Serial | 1850 | |||
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| Author | Ivet Rafegas; Javier Vazquez; Robert Benavente; Maria Vanrell; Susana Alvarez |
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| Title | Enhancing spatio-chromatic representation with more-than-three color coding for image description | Type | Journal Article | |||
| Year | 2017 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A | |
| Volume |
34 | Issue | 5 | Pages | 827-837 | |
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| Abstract | Extraction of spatio-chromatic features from color images is usually performed independently on each color channel. Usual 3D color spaces, such as RGB, present a high inter-channel correlation for natural images. This correlation can be reduced using color-opponent representations, but the spatial structure of regions with small color differences is not fully captured in two generic Red-Green and Blue-Yellow channels. To overcome these problems, we propose a new color coding that is adapted to the specific content of each image. Our proposal is based on two steps: (a) setting the number of channels to the number of distinctive colors we find in each image (avoiding the problem of channel correlation), and (b) building a channel representation that maximizes contrast differences within each color channel (avoiding the problem of low local contrast). We call this approach more-than-three color coding (MTT) to enhance the fact that the number of channels is adapted to the image content. The higher color complexity an image has, the more channels can be used to represent it. Here we select distinctive colors as the most predominant in the image, which we call color pivots, and we build the new color coding using these color pivots as a basis. To evaluate the proposed approach we measure its efficiency in an image categorization task. We show how a generic descriptor improves its performance at the description level when applied on the MTT coding. | |||||
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| Notes | CIC; 600.087 | Approved | no | |||
| Call Number | Admin @ si @ RVB2017 | Serial | 2892 | |||
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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 | Type | Journal Article | |||
| Year | 2013 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI | |
| 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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| ISSN | 0162-8828 | ISBN | Medium | |||
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| Notes | CIC; 600.051; 600.052; 605.203 | Approved | no | |||
| Call Number | Admin @ si @ MVO2013 | Serial | 2289 | |||
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| Author | C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger |
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| Title | Limitations of visual gamma corrections in LCD displays | Type | Journal Article | |||
| Year | 2014 | Publication | Displays | Abbreviated Journal | Dis | |
| Volume |
35 | Issue | 5 | Pages | 227–239 | |
| Keywords | Display calibration; Psychophysics; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration | |||||
| Abstract | A method for estimating the non-linear gamma transfer function of liquid–crystal displays (LCDs) without the need of a photometric measurement device was described by Xiao et al. (2011) [1]. It relies on observer’s judgments of visual luminance by presenting eight half-tone patterns with luminances from 1/9 to 8/9 of the maximum value of each colour channel. These half-tone patterns were distributed over the screen both over the vertical and horizontal viewing axes. We conducted a series of photometric and psychophysical measurements (consisting in the simultaneous presentation of half-tone patterns in each trial) to evaluate whether the angular dependency of the light generated by three different LCD technologies would bias the results of these gamma transfer function estimations. Our results show that there are significant differences between the gamma transfer functions measured and produced by observers at different viewing angles. We suggest appropriate modifications to the Xiao et al. paradigm to counterbalance these artefacts which also have the advantage of shortening the amount of time spent in collecting the psychophysical measurements. | |||||
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| Notes | CIC; DAG; 600.052; 600.077; 600.074 | Approved | no | |||
| Call Number | Admin @ si @ PRK2014 | Serial | 2511 | |||
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| Author | C. Alejandro Parraga; Javier Vazquez; Maria Vanrell |
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| Title | A new cone activation-based natural images dataset | Type | Journal Article | |||
| Year | 2009 | Publication | Perception | Abbreviated Journal | PER | |
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36 | Issue | Pages | 180 | ||
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| Abstract | We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website. | |||||
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ PVV2009 | Serial | 1193 | |||
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