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Author	Xavier Otazu; Maria Vanrell; C. Alejandro Parraga
Title	Multiresolution Wavelet Framework Models Brightness Induction Effects			Type	Journal
Year	2008	Publication	Vision Research	Abbreviated Journal	VR
Volume	48	Issue	5	Pages	733–751
Keywords
Abstract
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	CAT @ cat @ OVP2008a			Serial	927
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Author	Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell
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
Keywords
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;
Corporate Author				Thesis
Publisher	IEEE Computer Society	Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	0162-8828	ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ VBW2011			Serial	1715
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Author	Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
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
Keywords
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;
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	0162-8828	ISBN		Medium
Area		Expedition		Conference
Notes	CIC;ISE			Approved	no
Call Number	Admin @ si @ GGW2012			Serial	1850
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Author	Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco
Title	A Neurodynamical Model of Brightness Induction in V1			Type	Journal Article
Year	2013	Publication	PloS ONE	Abbreviated Journal	Plos
Volume	8	Issue	5	Pages	e64086
Keywords
Abstract	Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ POD2013			Serial	2242
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Author	C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC; DAG; 600.052; 600.077; 600.074			Approved	no
Call Number	Admin @ si @ PRK2014			Serial	2511
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Author	Ivet Rafegas; Javier Vazquez; Robert Benavente; Maria Vanrell; Susana Alvarez
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
Keywords
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC; 600.087			Approved	no
Call Number	Admin @ si @ RVB2017			Serial	2892
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Author	Naila Murray; Sandra Skaff; Luca Marchesotti; Florent Perronnin
Title	Towards automatic and flexible concept transfer			Type	Journal Article
Year	2012	Publication	Computers and Graphics	Abbreviated Journal	CG
Volume	36	Issue	6	Pages	622–634
Keywords
Abstract	This paper introduces a novel approach to automatic, yet flexible, image concepttransfer; examples of concepts are “romantic”, “earthy”, and “luscious”. The presented method modifies the color content of an input image given only a concept specified by a user in natural language, thereby requiring minimal user input. This method is particularly useful for users who are aware of the message they wish to convey in the transferred image while being unsure of the color combination needed to achieve the corresponding transfer. Our framework is flexible for two reasons. First, the user may select one of two modalities to map input image chromaticities to target concept chromaticities depending on the level of photo-realism required. Second, the user may adjust the intensity level of the concepttransfer to his/her liking with a single parameter. The proposed method uses a convex clustering algorithm, with a novel pruning mechanism, to automatically set the complexity of models of chromatic content. Results show that our approach yields transferred images which effectively represent concepts as confirmed by a user study.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	0097-8493	ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ MSM2012			Serial	2002
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Author	Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg
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
Keywords
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.
Address
Corporate Author				Thesis
Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	0932-8092	ISBN		Medium
Area		Expedition		Conference
Notes	CIC; LAMP; 600.074; 600.079			Approved	no
Call Number	Admin @ si @ KBW2014			Serial	2510
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Author	Javier Vazquez; J. Kevin O'Regan; Maria Vanrell; Graham D. Finlayson
Title	A new spectrally sharpened basis to predict colour naming, unique hues, and hue cancellation			Type	Journal Article
Year	2012	Publication	Journal of Vision	Abbreviated Journal	VSS
Volume	12	Issue	6 (7)	Pages	1-14
Keywords
Abstract	When light is reflected off a surface, there is a linear relation between the three human photoreceptor responses to the incoming light and the three photoreceptor responses to the reflected light. Different colored surfaces have different linear relations. Recently, Philipona and O'Regan (2006) showed that when this relation is singular in a mathematical sense, then the surface is perceived as having a highly nameable color. Furthermore, white light reflected by that surface is perceived as corresponding precisely to one of the four psychophysically measured unique hues. However, Philipona and O'Regan's approach seems unrelated to classical psychophysical models of color constancy. In this paper we make this link. We begin by transforming cone sensors to spectrally sharpened counterparts. In sharp color space, illumination change can be modeled by simple von Kries type scalings of response values within each of the spectrally sharpened response channels. In this space, Philipona and O'Regan's linear relation is captured by a simple Land-type color designator defined by dividing reflected light by incident light. This link between Philipona and O'Regan's theory and Land's notion of color designator gives the model biological plausibility. We then show that Philipona and O'Regan's singular surfaces are surfaces which are very close to activating only one or only two of such newly defined spectrally sharpened sensors, instead of the usual three. Closeness to zero is quantified in a new simplified measure of singularity which is also shown to relate to the chromaticness of colors. As in Philipona and O'Regan's original work, our new theory accounts for a large variety of psychophysical color data.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ VOV2012			Serial	1998
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Author	Trevor Canham; Javier Vazquez; Elise Mathieu; Marcelo Bertalmío
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
Keywords
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ CVM2021			Serial	3595
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Author	Graham D. Finlayson; Javier Vazquez; Sabine Süsstrunk; Maria Vanrell
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
Keywords
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	1084-7529	ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ FVS2012			Serial	2000
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Author	Fahad Shahbaz Khan; Joost Van de Weijer; Muhammad Anwer Rao; Michael Felsberg; Carlo Gatta
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
Keywords
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	1057-7149	ISBN		Medium
Area		Expedition		Conference
Notes	CIC; LAMP; 601.160; 600.074; 600.079;MILAB			Approved	no
Call Number	Admin @ si @ KWR2014			Serial	2507
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Author	Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	1057-7149	ISBN		Medium
Area		Expedition		Conference
Notes	ISE;CIC			Approved	no
Call Number	Admin @ si @ GGW2011			Serial	1717
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Author	Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco
Title	Brightness induction by contextual influences in V1: a neurodynamical account			Type	Abstract
Year	2012	Publication	Journal of Vision	Abbreviated Journal	VSS
Volume	12	Issue	9	Pages
Keywords
Abstract	Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas and reveals fundamental properties of neural organization in the visual system. Several phenomenological models have been proposed that successfully account for psychophysical data (Pessoa et al. 1995, Blakeslee and McCourt 2004, Barkan et al. 2008, Otazu et al. 2008). Neurophysiological evidence suggests that brightness information is explicitly represented in V1 and neuronal response modulations have been observed followingluminance changes outside their receptive fields (Rossi and Paradiso, 1999). In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (1999) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2–3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant effect of contextual influences. In our model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition which makes it possible to recover an image reflecting the perceived intensity. The proposed model successfully accounts for well known pyschophysical effects (among them: the White's and modified White's effects, the Todorović, Chevreul, achromatic ring patterns, and grating induction effects). Our work suggests that intra-cortical interactions in the primary visual cortex could partially explain perceptual brightness induction effects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual pathway.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	CIC			Approved	no
Call Number	Admin @ si @ OPD2012b			Serial	2178
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Author	Xavier Otazu; Olivier Penacchio; Xim Cerda-Company
Title	Brightness and colour induction through contextual influences in V1			Type	Conference Article
Year	2015	Publication	Scottish Vision Group 2015 SGV2015	Abbreviated Journal
Volume	12	Issue	9	Pages	1208-2012
Keywords
Abstract
Address	Carnoustie; Scotland; March 2015
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference	SGV
Notes	NEUROBIT;CIC			Approved	no
Call Number	Admin @ si @ OPC2015a			Serial	2632
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Author	Jaykishan Patel; Alban Flachot; Javier Vazquez; David H. Brainard; Thomas S. A. Wallis; Marcus A. Brubaker; Richard F. Murray
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
Keywords
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.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference
Notes	MACO; CIC			Approved	no
Call Number	Admin @ si @ PFV2023			Serial	3890
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Author	Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
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
Keywords
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
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	1077-3142	ISBN		Medium
Area		Expedition		Conference
Notes	CAT;CIC			Approved	no
Call Number	Admin @ si @ ASV2012			Serial	1827
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