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Author |
Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich |
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Title |
Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset |
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Journal Article |
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Year |
2009 |
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Journal of Imaging Science and Technology |
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Volume |
53 |
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3 |
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031105–9 |
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The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene. |
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no |
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CAT @ cat @ VPV2009a |
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1171 |
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Author |
C. Alejandro Parraga; Ramon Baldrich; Maria Vanrell |
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Title |
Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset |
Type |
Conference Article |
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Year |
2010 |
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5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
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50–57 |
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The characterization of trichromatic cameras is usually done in terms of a device-independent color space, such as the CIE 1931 XYZ space. This is indeed convenient since it allows the testing of results against colorimetric measures. We have characterized our camera to represent human cone activation by mapping the camera sensor's (RGB) responses to human (LMS) through a polynomial transformation, which can be “customized” according to the types of scenes we want to represent. Here we present a method to test the accuracy of the camera measures and a study on how the choice of training reflectances for the polynomial may alter the results. |
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Joensuu, Finland |
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9781617388897 |
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CGIV/MCS |
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CAT @ cat @ PBV2010a |
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1322 |
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Author |
C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell |
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Title |
Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels |
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Journal Article |
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Year |
2011 |
Publication |
Perception |
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PER |
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40 |
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96 |
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The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle. |
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Admin @ si @ PPV2011 |
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1720 |
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Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell |
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Title |
Local Perceptual Weighting in JPEG2000 for Color Images |
Type |
Conference Article |
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Year |
2010 |
Publication |
5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
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255–260 |
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The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM (Chromatic Induction Wavelet Model). |
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Joensuu, Finland |
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9781617388897 |
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CGIV/MCS |
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CIC |
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no |
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CAT @ cat @ MOV2010a |
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1307 |
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Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell |
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Title |
Contribution of CIWaM in JPEG2000 Quantization for Color Images |
Type |
Conference Article |
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Year |
2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
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132–136 |
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The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM(ChromaticInductionWaveletModel). |
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Gjovik (Norway) |
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CREATE |
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CIC |
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no |
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CAT @ cat @ MOV2010b |
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1308 |
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Author |
Susana Alvarez; Maria Vanrell |
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Title |
Texton theory revisited: a bag-of-words approach to combine textons |
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Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
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PR |
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45 |
Issue |
12 |
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4312-4325 |
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The aim of this paper is to revisit an old theory of texture perception and
update its computational implementation by extending it to colour. With this in mind we try to capture the optimality of perceptual systems. This is achieved in the proposed approach by sharing well-known early stages of the visual processes and extracting low-dimensional features that perfectly encode adequate properties for a large variety of textures without needing further learning stages. We propose several descriptors in a bag-of-words framework that are derived from different quantisation models on to the feature spaces. Our perceptual features are directly given by the shape and colour attributes of image blobs, which are the textons. In this way we avoid learning visual words and directly build the vocabularies on these lowdimensionaltexton spaces. Main differences between proposed descriptors rely on how co-occurrence of blob attributes is represented in the vocabularies. Our approach overcomes current state-of-art in colour texture description which is proved in several experiments on large texture datasets. |
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0031-3203 |
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CIC |
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no |
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Admin @ si @ AlV2012a |
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2130 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez |
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Title |
Color Attributes for Object Detection |
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Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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3306-3313 |
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pedestrian detection |
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State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape.
In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe-
art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods. |
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Providence; Rhode Island; USA; |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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ADAS; CIC; |
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no |
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Admin @ si @ KRW2012 |
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1935 |
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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 |
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2013 |
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20th IEEE International Conference on Image Processing |
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285 - 289 |
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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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ICIP |
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CIC; 600.048; 600.052; 600.051 |
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no |
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Admin @ si @ BSW2013 |
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2264 |
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Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
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Title |
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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LNCS |
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0302-9743 |
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978-3-319-27862-9 |
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ISVC |
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Admin @ si @ SMG2015 |
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2736 |
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Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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Saliency Estimation Using a Non-Parametric Low-Level Vision Model |
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Conference Article |
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2011 |
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IEEE conference on Computer Vision and Pattern Recognition |
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433-440 |
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Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms |
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Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. |
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Colorado Springs |
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1063-6919 |
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978-1-4577-0394-2 |
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CVPR |
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no |
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Admin @ si @ MVO2011 |
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1757 |
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Author |
C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Psychophysical measurements to model inter-colour regions of colour-naming space |
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Journal Article |
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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 |
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 |
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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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CIC; 600.052; 600.051; 600.074 |
Approved |
no |
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Call Number |
Admin @ si @ SPB2014 |
Serial |
2506 |
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Permanent link to this record |
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Author |
C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
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Title |
Towards a general model of colour categorization which considers context |
Type |
Journal Article |
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Year |
2010 |
Publication |
Perception. ECVP Abstract Supplement |
Abbreviated Journal |
PER |
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Volume |
39 |
Issue |
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Pages |
86 |
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Keywords |
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Abstract |
In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly dierent(more diuse) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we
completed our parametric fuzzy-sets model of colour naming space. |
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CIC |
Approved |
no |
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Call Number |
CAT @ cat @ PBV2010b |
Serial |
1326 |
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Permanent link to this record |
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Author |
Olivier Penacchio; C. Alejandro Parraga; Maria Vanrell |
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Title |
Natural Scene Statistics account for Human Cones Ratios |
Type |
Journal Article |
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Year |
2010 |
Publication |
Perception. ECVP Abstract Supplement |
Abbreviated Journal |
PER |
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Volume |
39 |
Issue |
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Pages |
101 |
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Keywords |
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Abstract |
In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly dierent(more diuse) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space. |
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Notes |
CIC |
Approved |
no |
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Call Number |
CAT @ cat @ PPV2010 |
Serial |
1357 |
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Permanent link to this record |