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Author	Jordi Roca; Maria Vanrell; C. Alejandro Parraga
Title	What is constant in colour constancy?			Type	Conference Article
Year	2012	Publication	6th European Conference on Colour in Graphics, Imaging and Vision	Abbreviated Journal
Volume		Issue		Pages	337-343
Keywords
Abstract	Color constancy refers to the ability of the human visual system to stabilize the color appearance of surfaces under an illuminant change. In this work we studied how the interrelations among nine colors are perceived under illuminant changes, particularly whether they remain stable across 10 different conditions (5 illuminants and 2 backgrounds). To do so we have used a paradigm that measures several colors under an immersive state of adaptation. From our measures we defined a perceptual structure descriptor that is up to 87% stable over all conditions, suggesting that color category features could be used to predict color constancy. This is in agreement with previous results on the stability of border categories [1,2] and with computational color constancy algorithms [3] for estimating the scene illuminant.
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	9781622767014	Medium
Area		Expedition		Conference	CGIV
Notes	CIC			Approved	no
Call Number	RVP2012			Serial	2189
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Author	Jaime Moreno; Xavier Otazu; Maria Vanrell
Title	Local Perceptual Weighting in JPEG2000 for Color Images			Type	Conference Article
Year	2010	Publication	5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science	Abbreviated Journal
Volume		Issue		Pages	255–260
Keywords
Abstract	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).
Address	Joensuu, Finland
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	9781617388897	Medium
Area		Expedition		Conference	CGIV/MCS
Notes	CIC			Approved	no
Call Number	CAT @ cat @ MOV2010a			Serial	1307
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Author	C. Alejandro Parraga; Ramon Baldrich; Maria Vanrell
Title	Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset			Type	Conference Article
Year	2010	Publication	5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science	Abbreviated Journal
Volume		Issue		Pages	50–57
Keywords
Abstract	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.
Address	Joensuu, Finland
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	9781617388897	Medium
Area		Expedition		Conference	CGIV/MCS
Notes	CIC			Approved	no
Call Number	CAT @ cat @ PBV2010a			Serial	1322
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Author	Javier Vazquez; G. D. Finlayson; Maria Vanrell
Title	A compact singularity function to predict WCS data and unique hues			Type	Conference Article
Year	2010	Publication	5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science	Abbreviated Journal
Volume		Issue		Pages	33–38
Keywords
Abstract	Understanding how colour is used by the human vision system is a widely studied research field. The field, though quite advanced, still faces important unanswered questions. One of them is the explanation of the unique hues and the assignment of color names. This problem addresses the fact of different perceptual status for different colors. Recently, Philipona and O'Regan have proposed a biological model that allows to extract the reflection properties of any surface independently of the lighting conditions. These invariant properties are the basis to compute a singularity index that predicts the asymmetries presented in unique hues and basic color categories psychophysical data, therefore is giving a further step in their explanation. In this paper we build on their formulation and propose a new singularity index. This new formulation equally accounts for the location of the 4 peaks of the World colour survey and has two main advantages. First, it is a simple elegant numerical measure (the Philipona measurement is a rather cumbersome formula). Second, we develop a colour-based explanation for the measure.
Address	Joensuu, Finland
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	9781617388897	Medium
Area		Expedition		Conference	CGIV/MCS
Notes	CIC			Approved	no
Call Number	CAT @ cat @ VFV2010			Serial	1324
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Author	Robert Benavente; C. Alejandro Parraga; Maria Vanrell
Title	La influencia del contexto en la definicion de las fronteras entre las categorias cromaticas			Type	Conference Article
Year	2010	Publication	9th Congreso Nacional del Color	Abbreviated Journal
Volume		Issue		Pages	92–95
Keywords	Categorización del color; Apariencia del color; Influencia del contexto; Patrones de Mondrian; Modelos paramétricos
Abstract	En este artículo presentamos los resultados de un experimento de categorización de color en el que las muestras se presentaron sobre un fondo multicolor (Mondrian) para simular los efectos del contexto. Los resultados se comparan con los de un experimento previo que, utilizando un paradigma diferente, determinó las fronteras sin tener en cuenta el contexto. El análisis de los resultados muestra que las fronteras obtenidas con el experimento en contexto presentan menos confusión que las obtenidas en el experimento sin contexto.
Address	Alicante (Spain)
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	978-84-9717-144-1	Medium
Area		Expedition		Conference	CNC
Notes	CIC			Approved	no
Call Number	CAT @ cat @ BPV2010			Serial	1327
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Author	A.Gonzalez; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga
Title	Coloresia: An Interactive Colour Perception Device for the Visually Impaired			Type	Book Chapter
Year	2013	Publication	Multimodal Interaction in Image and Video Applications	Abbreviated Journal
Volume	48	Issue		Pages	47-66
Keywords
Abstract	A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves.
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	1868-4394	ISBN	978-3-642-35931-6	Medium
Area		Expedition		Conference
Notes	CIC; 600.052; 605.203			Approved	no
Call Number	Admin @ si @ GBP2013			Serial	2266
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Author	Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich
Title	Perception Based Representations for Computational Colour			Type	Conference Article
Year	2011	Publication	3rd International Workshop on Computational Color Imaging	Abbreviated Journal
Volume	6626	Issue		Pages	16-30
Keywords	colour perception, induction, naming, psychophysical data, saliency, segmentation
Abstract	The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.
Address	Milan, Italy
Corporate Author				Thesis
Publisher	Springer-Verlag	Place of Publication		Editor	Raimondo Schettini, Shoji Tominaga, Alain Trémeau
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title	LNCS
Series Volume		Series Issue		Edition
ISSN		ISBN	978-3-642-20403-6	Medium
Area		Expedition		Conference	CCIW
Notes	CIC			Approved	no
Call Number	Admin @ si @ VMB2011			Serial	1733
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Author	Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
Title	3D Texton Spaces for color-texture retrieval			Type	Conference Article
Year	2010	Publication	7th International Conference on Image Analysis and Recognition	Abbreviated Journal
Volume	6111	Issue		Pages	354–363
Keywords
Abstract	Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel.
Address
Corporate Author				Thesis
Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	A.C. Campilho and M.S. Kamel
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title	LNCS
Series Volume		Series Issue		Edition
ISSN	0302-9743	ISBN	978-3-642-13771-6	Medium
Area		Expedition		Conference	ICIAR
Notes	CIC			Approved	no
Call Number	CAT @ cat @ ASV2010a			Serial	1325
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Author	Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich
Title	DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition			Type	Conference Article
Year	2015	Publication	Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II	Abbreviated Journal
Volume	9475	Issue		Pages	463-473
Keywords	Projector-camera systems; Feature descriptors; Object recognition
Abstract	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.
Address
Corporate Author				Thesis
Publisher	Springer International Publishing	Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title	LNCS
Series Volume		Series Issue		Edition
ISSN	0302-9743	ISBN	978-3-319-27862-9	Medium
Area		Expedition		Conference	ISVC
Notes	CIC			Approved	no
Call Number	Admin @ si @ SMG2015			Serial	2736
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Author	Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez
Title	Color Attributes for Object Detection			Type	Conference Article
Year	2012	Publication	25th IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
Volume		Issue		Pages	3306-3313
Keywords	pedestrian detection
Abstract	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.
Address	Providence; Rhode Island; USA;
Corporate Author				Thesis
Publisher	IEEE Xplore	Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	1063-6919	ISBN	978-1-4673-1226-4	Medium
Area		Expedition		Conference	CVPR
Notes	ADAS; CIC;			Approved	no
Call Number	Admin @ si @ KRW2012			Serial	1935
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Author	Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell
Title	Names and Shades of Color for Intrinsic Image Estimation			Type	Conference Article
Year	2012	Publication	25th IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
Volume		Issue		Pages	278-285
Keywords
Abstract	In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance.
Address	Providence, Rhode Island
Corporate Author				Thesis
Publisher	IEEE Xplore	Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN	1063-6919	ISBN	978-1-4673-1226-4	Medium
Area		Expedition		Conference	CVPR
Notes	CIC			Approved	no
Call Number	Admin @ si @ SPB2012			Serial	2026
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Author	Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga
Title	Saliency Estimation Using a Non-Parametric Low-Level Vision Model			Type	Conference Article
Year	2011	Publication	IEEE conference on Computer Vision and Pattern Recognition	Abbreviated Journal
Volume		Issue		Pages	433-440
Keywords	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
Abstract	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.
Address	Colorado Springs
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	1063-6919	ISBN	978-1-4577-0394-2	Medium
Area		Expedition		Conference	CVPR
Notes	CIC			Approved	no
Call Number	Admin @ si @ MVO2011			Serial	1757
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Author	Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
Title	Perceptual color texture codebooks for retrieving in highly diverse texture datasets			Type	Conference Article
Year	2010	Publication	20th International Conference on Pattern Recognition	Abbreviated Journal
Volume		Issue		Pages	866–869
Keywords
Abstract	Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel.
Address	Istanbul (Turkey)
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	1051-4651	ISBN	978-1-4244-7542-1	Medium
Area		Expedition		Conference	ICPR
Notes	CIC			Approved	no
Call Number	CAT @ cat @ ASV2010b			Serial	1426
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Author	Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell
Title	Top-Down Color Attention for Object Recognition			Type	Conference Article
Year	2009	Publication	12th International Conference on Computer Vision	Abbreviated Journal
Volume		Issue		Pages	979 - 986
Keywords
Abstract	Generally the bag-of-words based image representation follows a bottom-up paradigm. 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, combining multiple cues such as shape and color often provides below-expected results. This paper presents a novel method for recognizing object categories when using multiple cues by separating the shape and color cue. Color is used to guide attention by means of a top-down category-specific attention map. The color attention map is then further deployed to modulate the shape features by taking more features from regions within an image that are likely to contain an object instance. This procedure leads to a category-specific image histogram representation for each category. Furthermore, we argue that the method combines the advantages of both early and late fusion. We compare our approach with existing methods that combine color and shape cues on three data sets containing varied importance of both cues, namely, Soccer ( color predominance), Flower (color and shape parity), and PASCAL VOC Challenge 2007 (shape predominance). The experiments clearly demonstrate that in all three data sets our proposed framework significantly outperforms the state-of-the-art methods for combining color and shape information.
Address	Kyoto, Japan
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	1550-5499	ISBN	978-1-4244-4420-5	Medium
Area		Expedition		Conference	ICCV
Notes	CIC			Approved	no
Call Number	CAT @ cat @ SWV2009			Serial	1196
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