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| Author | Danna Xue; Javier Vazquez; Luis Herranz; Yang Zhang; Michael S Brown |
 
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| Title | Integrating High-Level Features for Consistent Palette-based Multi-image Recoloring | Type | Journal Article | |||
| Year | 2023 | Publication | Computer Graphics Forum | Abbreviated Journal  |
CGF | |
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| Abstract | Achieving visually consistent colors across multiple images is important when images are used in photo albums, websites, and brochures. Unfortunately, only a handful of methods address multi-image color consistency compared to one-to-one color transfer techniques. Furthermore, existing methods do not incorporate high-level features that can assist graphic designers in their work. To address these limitations, we introduce a framework that builds upon a previous palette-based color consistency method and incorporates three high-level features: white balance, saliency, and color naming. We show how these features overcome the limitations of the prior multi-consistency workflow and showcase the user-friendly nature of our framework. | |||||
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| Notes | CIC; MACO | Approved | no | |||
| Call Number | Admin @ si @ XVH2023 | Serial | 3883 | |||
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| Author | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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| Title | Low-dimensional and Comprehensive Color Texture Description | Type | Journal Article | |||
| Year | 2012 | Publication | Computer Vision and Image Understanding | Abbreviated Journal |
CVIU | |
| Volume | 116 | Issue | I | Pages | 54-67 | |
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| Abstract | Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are defined independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges).
A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent definition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz’s Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is defined from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap |
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| ISSN | 1077-3142 | ISBN | Medium | |||
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| Notes | CAT;CIC | Approved | no | |||
| Call Number | Admin @ si @ ASV2012 | Serial | 1827 | |||
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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 | Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva |
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| Title | Colour Normalisation Based on Background Information. | Type | Miscellaneous | |||
| Year | 2001 | Publication | Proceeding ICIP 2001, IEEE International Conference on Image Processing | Abbreviated Journal |
ICIP 2001 | |
| Volume | Issue | 1 | Pages | 874–877 | ||
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| Address | Grecia. | |||||
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| Notes | ADAS;DAG;CIC | Approved | no | |||
| Call Number | ADAS @ adas @ VLP2001 | Serial | 167 | |||
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| Author | Xavier Boix; Josep M. Gonfaus; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez |
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| Title | Harmony Potentials: Fusing Global and Local Scale for Semantic Image Segmentation | Type | Journal Article | |||
| Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal |
IJCV | |
| Volume | 96 | Issue | 1 | Pages | 83-102 | |
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| Abstract | The Hierarchical Conditional Random Field(HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF models of image segmentation do not allow multiple classes to be assigned to a single region, which limits their ability to incorporate contextual information across multiple scales.
At higher scales in the image, this representation yields an oversimpli ed model since multiple classes can be reasonably expected to appear within large regions. This simpli ed model particularly limits the impact of information at higher scales. Since class-label information at these scales is usually more reliable than at lower, noisier scales, neglecting this information is undesirable. To address these issues, we propose a new consistency potential for image labeling problems, which we call the harmony potential. It can encode any possible combi- nation of labels, penalizing only unlikely combinations of classes. We also propose an e ective sampling strategy over this expanded label set that renders tractable the underlying optimization problem. Our approach obtains state-of-the-art results on two challenging, standard benchmark datasets for semantic image segmentation: PASCAL VOC 2010, and MSRC-21. |
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| ISSN | 0920-5691 | ISBN | Medium | |||
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| Notes | ISE;CIC;ADAS | Approved | no | |||
| Call Number | Admin @ si @ BGW2012 | Serial | 1718 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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| Title | Modulating Shape Features by Color Attention for Object Recognition | Type | Journal Article | |||
| Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal |
IJCV | |
| Volume | 98 | Issue | 1 | Pages | 49-64 | |
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| Abstract | Bag-of-words based image representation is a successful approach for object recognition. Generally, the subsequent stages of the process: feature detection,feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom up and top-down attention maps. Subsequently, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information. | |||||
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| Publisher | Springer Netherlands | Place of Publication | Editor | |||
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| ISSN | 0920-5691 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ KWV2012 | Serial | 1864 | |||
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| Author | Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
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| Title | Coloring Action Recognition in Still Images | Type | Journal Article | |||
| Year | 2013 | Publication | International Journal of Computer Vision | Abbreviated Journal |
IJCV | |
| Volume | 105 | Issue | 3 | Pages | 205-221 | |
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| Abstract | In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. | |||||
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| Publisher | Springer US | Place of Publication | Editor | |||
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| ISSN | 0920-5691 | ISBN | Medium | |||
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| Notes | CIC; ADAS; 600.057; 600.048 | Approved | no | |||
| Call Number | Admin @ si @ KRW2013 | Serial | 2285 | |||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke |
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| Title | A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores | Type | Journal Article | |||
| Year | 2010 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal |
IJDAR | |
| Volume | 13 | Issue | 4 | Pages | 243-259 | |
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| Abstract | The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers. | |||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1433-2833 | ISBN | Medium | |||
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| Notes | DAG; CAT;CIC | Approved | no | |||
| Call Number | FLS2010b | Serial | 1319 | |||
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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 | |
| Volume | 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 | |
| Volume | 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 | 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 | Hassan Ahmed Sial; Ramon Baldrich; Maria Vanrell |
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| Title | Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects | Type | Journal Article | |||
| Year | 2020 | Publication | Journal of the Optical Society of America A | Abbreviated Journal |
JOSA A | |
| Volume | 37 | Issue | 1 | Pages | 1-15 | |
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| Abstract | Estimation of intrinsic images still remains a challenging task due to weaknesses of ground-truth datasets, which either are too small or present non-realistic issues. On the other hand, end-to-end deep learning architectures start to achieve interesting results that we believe could be improved if important physical hints were not ignored. In this work, we present a twofold framework: (a) a flexible generation of images overcoming some classical dataset problems such as larger size jointly with coherent lighting appearance; and (b) a flexible architecture tying physical properties through intrinsic losses. Our proposal is versatile, presents low computation time, and achieves state-of-the-art results. | |||||
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| Notes | CIC; 600.140; 600.12; 600.118 | Approved | no | |||
| Call Number | Admin @ si @ SBV2019 | Serial | 3311 | |||
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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 | |
| Volume | 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 | 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 | |
| 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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| Notes | CIC; 600.052; 600.051; 605.203 | Approved | no | |||
| Call Number | Admin @ si @ RPV2013 | Serial | 2288 | |||
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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 | Olivier Penacchio |
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| Title | Mixed Hodge Structures and Equivariant Sheaves on the Projective Plane | Type | Journal Article | |||
| Year | 2011 | Publication | Mathematische Nachrichten | Abbreviated Journal |
MN | |
| Volume | 284 | Issue | 4 | Pages | 526-542 | |
| Keywords | Mixed Hodge structures, equivariant sheaves, MSC (2010) Primary: 14C30, Secondary: 14F05, 14M25 | |||||
| Abstract | We describe an equivalence of categories between the category of mixed Hodge structures and a category of equivariant vector bundles on a toric model of the complex projective plane which verify some semistability condition. We then apply this correspondence to define an invariant which generalizes the notion of R-split mixed Hodge structure and give calculations for the first group of cohomology of possibly non smooth or non-complete curves of genus 0 and 1. Finally, we describe some extension groups of mixed Hodge structures in terms of equivariant extensions of coherent sheaves. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim | |||||
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| Publisher | WILEY-VCH Verlag | Place of Publication | Editor | R. Mennicken | ||
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| ISSN | 1522-2616 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Pen2011 | Serial | 1721 | |||
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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 | |
| Volume | 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 | Javier Vazquez; C. Alejandro Parraga; Maria Vanrell |
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| Title | Ordinal pairwise method for natural images comparison | Type | Journal Article | |||
| Year | 2009 | Publication | Perception | Abbreviated Journal |
PER | |
| Volume | 38 | Issue | Pages | 180 | ||
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| Abstract | 38(Suppl.)ECVP Abstract Supplement
We developed a new psychophysical method to compare different colour appearance models when applied to natural scenes. The method was as follows: two images (processed by different algorithms) were displayed on a CRT monitor and observers were asked to select the most natural of them. The original images were gathered by means of a calibrated trichromatic digital camera and presented one on top of the other on a calibrated screen. The selection was made by pressing on a 6-button IR box, which allowed observers to consider not only the most natural but to rate their selection. The rating system allowed observers to register how much more natural was their chosen image (eg, much more, definitely more, slightly more), which gave us valuable extra information on the selection process. The results were analysed considering both the selection as a binary choice (using Thurstone's law of comparative judgement) and using Bradley-Terry method for ordinal comparison. Our results show a significant difference in the rating scales obtained. Although this method has been used in colour constancy algorithm comparisons, its uses are much wider, eg to compare algorithms of image compression, rendering, recolouring, etc. |
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ VPV2009b | Serial | 1191 | |||
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