Publicacions CVC -- Query Results

[1–10] << 11 12 13 >>

Details

Records
Author	Fahad Shahbaz Khan
Title	Coloring bag-of-words based image representations			Type	Book Whole
Year	2011	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
Volume		Issue		Pages
Keywords
Abstract	Put succinctly, the bag-of-words based image representation is the most successful approach for object and scene recognition. Within the bag-of-words framework the optimal fusion of multiple cues, such as shape, texture and color, still remains an active research domain. There exist two main approaches to combine color and shape information within the bag-of-words framework. The first approach called, early fusion, fuses color and shape at the feature level as a result of which a joint colorshape vocabulary is produced. The second approach, called late fusion, concatenates histogram representation of both color and shape, obtained independently. In the first part of this thesis, we analyze the theoretical implications of both early and late feature fusion. We demonstrate that both these approaches are suboptimal for a subset of object categories. Consequently, we propose a novel method for recognizing object categories when using multiple 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, the color attention maps are used to modulate the weights of the shape features. Shape features are given more weight in regions with higher attention and vice versa. The approach is tested on several benchmark object recognition data sets and the results clearly demonstrate the effectiveness of our proposed method. In the second part of the thesis, we investigate the problem of obtaining compact spatial pyramid representations for object and scene recognition. Spatial pyramids have been successfully applied to incorporate spatial information into bag-of-words based image representation. However, a major drawback of spatial pyramids is that it leads to high dimensional image representations. We present a novel framework for obtaining compact pyramid representation. The approach reduces the size of a high dimensional pyramid representation upto an order of magnitude without any significant reduction in accuracy. Moreover, we also investigate the optimal combination of multiple features such as color and shape within the context of our compact pyramid representation. Finally, we describe a novel technique to build discriminative visual words from multiple cues learned independently from training images. To this end, we use an information theoretic vocabulary compression technique to find discriminative combinations of visual cues and the resulting visual vocabulary is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. The approach is tested on standard object recognition data sets. The results obtained clearly demonstrate the effectiveness of our approach.
Address
Corporate Author				Thesis	Ph.D. thesis
Publisher		Place of Publication		Editor	Joost Van de Weijer;Maria Vanrell
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 @ Kha2011			Serial	1838
Permanent link to this record



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
Permanent link to this record



Author	Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell
Title	Portmanteau Vocabularies for Multi-Cue Image Representation			Type	Conference Article
Year	2011	Publication	25th Annual Conference on Neural Information Processing Systems	Abbreviated Journal
Volume		Issue		Pages
Keywords
Abstract	We describe a novel technique for feature combination in the bag-of-words model of image classification. Our approach builds discriminative compound words from primitive cues learned independently from training images. Our main observation is that modeling joint-cue distributions independently is more statistically robust for typical classification problems than attempting to empirically estimate the dependent, joint-cue distribution directly. We use Information theoretic vocabulary compression to find discriminative combinations of cues and the resulting vocabulary of portmanteau words is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. State-of-the-art results on both the Oxford Flower-102 and Caltech-UCSD Bird-200 datasets demonstrate the effectiveness of our technique compared to other, significantly more complex approaches to multi-cue image representation
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	NIPS
Notes	CIC			Approved	no
Call Number	Admin @ si @ KWB2011			Serial	1865
Permanent link to this record



Author	Naila Murray; Sandra Skaff; Luca Marchesotti; Florent Perronnin
Title	Towards Automatic Concept Transfer			Type	Conference Article
Year	2011	Publication	Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering	Abbreviated Journal
Volume		Issue		Pages	167.176
Keywords	chromatic modeling, color concepts, color transfer, concept transfer
Abstract	This paper introduces a novel approach to automatic concept transfer; examples of concepts are “romantic”, “earthy”, and “luscious”. The approach 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 approach 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. The user may adjust the intensity level of the concept transfer to his/her liking with a single parameter. The proposed approach uses a convex clustering algorithm, with a novel pruning mechanism, to automatically set the complexity of models of chromatic content. It also uses the Earth-Mover's Distance to compute a mapping between the models of the input image and the target chromatic concept. Results show that our approach yields transferred images which effectively represent concepts, as confirmed by a user study.
Address
Corporate Author				Thesis
Publisher	ACM Press	Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title		Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN	978-1-4503-0907-3	Medium
Area		Expedition		Conference	NPAR
Notes	CIC			Approved	no
Call Number	Admin @ si @ MSM2011			Serial	1866
Permanent link to this record



Author	Jordi Roca; C. Alejandro Parraga; Maria Vanrell
Title	Categorical Focal Colours are Structurally Invariant Under Illuminant Changes			Type	Conference Article
Year	2011	Publication	European Conference on Visual Perception	Abbreviated Journal
Volume		Issue		Pages	196
Keywords
Abstract	The visual system perceives the colour of surfaces approximately constant under changes of illumination. In this work, we investigate how stable is the perception of categorical \“focal\” colours and their interrelations with varying illuminants and simple chromatic backgrounds. It has been proposed that best examples of colour categories across languages cluster in small regions of the colour space and are restricted to a set of 11 basic terms (Kay and Regier, 2003 Proceedings of the National Academy of Sciences of the USA 100 9085\–9089). Following this, we developed a psychophysical paradigm that exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. The experiment was run on a CRT monitor (inside a dark room) under various simulated illuminants. We modelled the recorded data for each subject and adapted state as a 3D interconnected structure (graph) in Lab space. The graph nodes were the subject\’s focal colours at each adaptation state. The model allowed us to get a better distance measure between focal structures under different illuminants. We found that perceptual focal structures tend to be preserved better than the structures of the physical \“ideal\” colours under illuminant changes.
Address
Corporate Author				Thesis
Publisher		Place of Publication		Editor
Language		Summary Language		Original Title
Series Editor		Series Title	Perception 40	Abbreviated Series Title
Series Volume		Series Issue		Edition
ISSN		ISBN		Medium
Area		Expedition		Conference	ECVP
Notes	CIC			Approved	no
Call Number	Admin @ si @ RPV2011			Serial	1867
Permanent link to this record



Author	Naila Murray; Luca Marchesotti; Florent Perronnin
Title	AVA: A Large-Scale Database for Aesthetic Visual Analysis			Type	Conference Article
Year	2012	Publication	25th IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
Volume		Issue		Pages	2408-2415
Keywords
Abstract	With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks
Address	Providence, Rhode Islan
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 @ MMP2012a			Serial	2025
Permanent link to this record



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
Permanent link to this record



Author	Naila Murray; Luca Marchesotti; Florent Perronnin
Title	Learning to Rank Images using Semantic and Aesthetic Labels			Type	Conference Article
Year	2012	Publication	23rd British Machine Vision Conference	Abbreviated Journal
Volume		Issue		Pages	110.1-110.10
Keywords
Abstract	Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one.
Address	Guildford, London
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	1-901725-46-4	Medium
Area		Expedition		Conference	BMVC
Notes	CIC			Approved	no
Call Number	Admin @ si @ MMP2012b			Serial	2027
Permanent link to this record



Author	Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus
Title	Color Naming			Type	Book Chapter
Year	2012	Publication	Color in Computer Vision: Fundamentals and Applications	Abbreviated Journal
Volume		Issue	17	Pages	287-317
Keywords
Abstract
Address
Corporate Author				Thesis
Publisher	John Wiley & Sons, Ltd.	Place of Publication		Editor	Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek
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 @ WBV2012			Serial	2063
Permanent link to this record



Author	Shida Beigpour
Title	Illumination and object reflectance modeling			Type	Book Whole
Year	2013	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
Volume		Issue		Pages
Keywords
Abstract	More realistic and accurate models of the scene illumination and object reflectance can greatly improve the quality of many computer vision and computer graphics tasks. Using such model, a more profound knowledge about the interaction of light with object surfaces can be established which proves crucial to a variety of computer vision applications. In the current work, we investigate the various existing approaches to illumination and reflectance modeling and form an analysis on their shortcomings in capturing the complexity of real-world scenes. Based on this analysis we propose improvements to different aspects of reflectance and illumination estimation in order to more realistically model the real-world scenes in the presence of complex lighting phenomena (i.e, multiple illuminants, interreflections and shadows). Moreover, we captured our own multi-illuminant dataset which consists of complex scenes and illumination conditions both outdoor and in laboratory conditions. In addition we investigate the use of synthetic data to facilitate the construction of datasets and improve the process of obtaining ground-truth information.
Address	Barcelona
Corporate Author				Thesis	Ph.D. thesis
Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Joost Van de Weijer;Ernest Valveny
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 @ Bei2013			Serial	2267
Permanent link to this record



Author	Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet
Title	Towards multispectral data acquisition with hand-held devices			Type	Conference Article
Year	2013	Publication	20th IEEE International Conference on Image Processing	Abbreviated Journal
Volume		Issue		Pages	2053 - 2057
Keywords	Multispectral; mobile devices; color measurements
Abstract	We propose a method to acquire multispectral data with handheld devices with front-mounted RGB cameras. We propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results are promising and show that the accuracy of the spectral reconstruction improves in the range from 30-40% over the spectral reconstruction based on a single illuminant. Furthermore, we propose to compute sensor-illuminant aware linear basis by discarding the part of the reflectances that falls in the sensorilluminant null-space. We show experimentally that optimizing reflectance estimation on these new basis functions decreases the RMSE significantly over basis functions that are independent to sensor-illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops, opening up applications which are currently considered to be unrealistic.
Address	Melbourne; Australia; September 2013
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	ICIP
Notes	CIC; DAG; 600.048			Approved	no
Call Number	Admin @ si @ KWK2013b			Serial	2265
Permanent link to this record



Author	Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras
Title	Intrinsic Image Evaluation On Synthetic Complex Scenes			Type	Conference Article
Year	2013	Publication	20th IEEE International Conference on Image Processing	Abbreviated Journal
Volume		Issue		Pages	285 - 289
Keywords
Abstract	Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes.
Address	Melbourne; Australia; September 2013
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	ICIP
Notes	CIC; 600.048; 600.052; 600.051			Approved	no
Call Number	Admin @ si @ BSW2013			Serial	2264
Permanent link to this record



Author	Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat
Title	Discriminative Color Descriptors			Type	Conference Article
Year	2013	Publication	IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
Volume		Issue		Pages	2866 - 2873
Keywords
Abstract	Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200.
Address	Portland; Oregon; June 2013
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		Medium
Area		Expedition		Conference	CVPR
Notes	CIC; 600.048			Approved	no
Call Number	Admin @ si @ KWK2013a			Serial	2262
Permanent link to this record



Author	Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier
Title	Automatic text localisation in scanned comic books			Type	Conference Article
Year	2013	Publication	Proceedings of the International Conference on Computer Vision Theory and Applications	Abbreviated Journal
Volume		Issue		Pages	814-819
Keywords	Text localization; comics; text/graphic separation; complex background; unstructured document
Abstract	Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented.
Address	Barcelona; February 2013
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	VISAPP
Notes	DAG; CIC; 600.056			Approved	no
Call Number	Admin @ si @ RKW2013b			Serial	2261
Permanent link to this record



Author	Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier
Title	An active contour model for speech balloon detection in comics			Type	Conference Article
Year	2013	Publication	12th International Conference on Document Analysis and Recognition	Abbreviated Journal
Volume		Issue		Pages	1240-1244
Keywords
Abstract	Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented.
Address	washington; USA; August 2013
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	1520-5363	ISBN		Medium
Area		Expedition		Conference	ICDAR
Notes	DAG; CIC; 600.056			Approved	no
Call Number	Admin @ si @ RKW2013a			Serial	2260
Permanent link to this record



Author	Alicia Fornes; Xavier Otazu; Josep Llados
Title	Show through cancellation and image enhancement by multiresolution contrast processing			Type	Conference Article
Year	2013	Publication	12th International Conference on Document Analysis and Recognition	Abbreviated Journal
Volume		Issue		Pages	200-204
Keywords
Abstract	Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities.
Address	Washington; USA; August 2013
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	1520-5363	ISBN		Medium
Area		Expedition		Conference	ICDAR
Notes	DAG; 602.006; 600.045; 600.061; 600.052;CIC			Approved	no
Call Number	Admin @ si @ FOL2013			Serial	2241
Permanent link to this record



Author	Javier Vazquez; Robert Benavente; Maria Vanrell
Title	Naming constraints constancy			Type	Conference Article
Year	2012	Publication	2nd Joint AVA / BMVA Meeting on Biological and Machine Vision	Abbreviated Journal
Volume		Issue		Pages
Keywords
Abstract	Different studies have shown that languages from industrialized cultures share a set of 11 basic colour terms: red, green, blue, yellow, pink, purple, brown, orange, black, white, and grey (Berlin & Kay, 1969, Basic Color Terms, University of California Press)( Kay & Regier, 2003, PNAS, 100, 9085-9089). Some of these studies have also reported the best representatives or focal values of each colour (Boynton and Olson, 1990, Vision Res. 30,1311–1317), (Sturges and Whitfield, 1995, CRA, 20:6, 364–376). Some further studies have provided us with fuzzy datasets for color naming by asking human observers to rate colours in terms of membership values (Benavente -et al-, 2006, CRA. 31:1, 48–56,). Recently, a computational model based on these human ratings has been developed (Benavente -et al-, 2008, JOSA-A, 25:10, 2582-2593). This computational model follows a fuzzy approach to assign a colour name to a particular RGB value. For example, a pixel with a value (255,0,0) will be named 'red' with membership 1, while a cyan pixel with a RGB value of (0, 200, 200) will be considered to be 0.5 green and 0.5 blue. In this work, we show how this colour naming paradigm can be applied to different computer vision tasks. In particular, we report results in colour constancy (Vazquez-Corral -et al-, 2012, IEEE TIP, in press) showing that the classical constraints on either illumination or surface reflectance can be substituted by the statistical properties encoded in the colour names. [Supported by projects TIN2010-21771-C02-1, CSD2007-00018].
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	AV A
Notes	CIC			Approved	no
Call Number	Admin @ si @ VBV2012			Serial	2131
Permanent link to this record



Author	Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco
Title	An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction			Type	Conference Article
Year	2012	Publication	2nd Joint AVA / BMVA Meeting on Biological and Machine Vision	Abbreviated Journal
Volume		Issue		Pages
Keywords
Abstract	Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. 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 (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) 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 visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM). This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here.
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	AV A
Notes	CIC			Approved	no
Call Number	Admin @ si @ OPD2012a			Serial	2132
Permanent link to this record