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Author M. Danelljan; Fahad Shahbaz Khan; Michael Felsberg; Joost Van de Weijer edit   pdf
doi  openurl
Title Adaptive color attributes for real-time visual tracking Type Conference Article
Year (down) 2014 Publication 27th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
Volume Issue Pages 1090 - 1097  
Keywords  
Abstract Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object
recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally
efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power.
This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional
variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms
state-of-the-art tracking methods while running at more than 100 frames per second.
 
Address Nottingham; UK; September 2014  
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 CVPR  
Notes CIC; LAMP; 600.074; 600.079 Approved no  
Call Number Admin @ si @ DKF2014 Serial 2509  
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Author Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg edit  doi
openurl 
Title Painting-91: A Large Scale Database for Computational Painting Categorization Type Journal Article
Year (down) 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 C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger edit   pdf
url  doi
openurl 
Title Limitations of visual gamma corrections in LCD displays Type Journal Article
Year (down) 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 C. Alejandro Parraga edit  doi
isbn  openurl
Title Color Vision, Computational Methods for Type Book Chapter
Year (down) 2014 Publication Encyclopedia of Computational Neuroscience Abbreviated Journal  
Volume Issue Pages 1-11  
Keywords Color computational vision; Computational neuroscience of color  
Abstract The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments.  
Address  
Corporate Author Thesis  
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor Dieter Jaeger; Ranu Jung  
Language Summary Language Original Title  
Series Editor Series Title Abbreviated Series Title  
Series Volume Series Issue Edition  
ISSN ISBN 978-1-4614-7320-6 Medium  
Area Expedition Conference  
Notes CIC; 600.074 Approved no  
Call Number Admin @ si @ Par2014 Serial 2512  
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Author Ricard Balague edit  openurl
Title Exploring the combination of color cues for intrinsic image decomposition Type Report
Year (down) 2014 Publication CVC Technical Report Abbreviated Journal  
Volume 178 Issue Pages  
Keywords  
Abstract Intrinsic image decomposition is a challenging problem that consists in separating an image into its physical characteristics: reflectance and shading. This problem can be solved in different ways, but most methods have combined information from several visual cues. In this work we describe an extension of an existing method proposed by Serra et al. which considers two color descriptors and combines them by means of a Markov Random Field. We analyze in depth the weak points of the method and we explore more possibilities to use in both descriptors. The proposed extension depends on the combination of the cues considered to overcome some of the limitations of the original method. Our approach is tested on the MIT dataset and Beigpour et al. dataset, which contain images of real objects acquired under controlled conditions and synthetic images respectively, with their corresponding ground truth.  
Address UAB; September 2014  
Corporate Author Thesis Master's 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; 600.074 Approved no  
Call Number Admin @ si @ Bal2014 Serial 2579  
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Author Joost Van de Weijer; Fahad Shahbaz Khan edit   pdf
doi  isbn
openurl 
Title Fusing Color and Shape for Bag-of-Words Based Object Recognition Type Conference Article
Year (down) 2013 Publication 4th Computational Color Imaging Workshop Abbreviated Journal  
Volume 7786 Issue Pages 25-34  
Keywords Object Recognition; color features; bag-of-words; image classification  
Abstract In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research.  
Address Chiba; Japan; March 2013  
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 0302-9743 ISBN 978-3-642-36699-4 Medium  
Area Expedition Conference CCIW  
Notes CIC; 600.048 Approved no  
Call Number Admin @ si @ WeK2013 Serial 2283  
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Author Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana edit   pdf
doi  isbn
openurl 
Title Interactive Visual and Semantic Image Retrieval Type Book Chapter
Year (down) 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
Volume 48 Issue Pages 31-35  
Keywords  
Abstract One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results.  
Address  
Corporate Author Thesis  
Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria  
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; 605.203; 600.048 Approved no  
Call Number Admin @ si @ WKC2013 Serial 2284  
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Author Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg edit   pdf
doi  openurl
Title Coloring Action Recognition in Still Images Type Journal Article
Year (down) 2013 Publication International Journal of Computer Vision Abbreviated Journal IJCV  
Volume 105 Issue 3 Pages 205-221  
Keywords  
Abstract In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification.  
Address  
Corporate Author Thesis  
Publisher Springer US Place of Publication Editor  
Language Summary Language Original Title  
Series Editor Series Title Abbreviated Series Title  
Series Volume Series Issue Edition  
ISSN 0920-5691 ISBN Medium  
Area Expedition Conference  
Notes CIC; ADAS; 600.057; 600.048 Approved no  
Call Number Admin @ si @ KRW2013 Serial 2285  
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Author Jordi Roca; C. Alejandro Parraga; Maria Vanrell edit   pdf
doi  openurl
Title Chromatic settings and the structural color constancy index Type Journal Article
Year (down) 2013 Publication Journal of Vision Abbreviated Journal JV  
Volume 13 Issue 4-3 Pages 1-26  
Keywords  
Abstract Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects.  
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; 600.052; 600.051; 605.203 Approved no  
Call Number Admin @ si @ RPV2013 Serial 2288  
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Author Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga edit   pdf
doi  openurl
Title Low-level SpatioChromatic Grouping for Saliency Estimation Type Journal Article
Year (down) 2013 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
Volume 35 Issue 11 Pages 2810-2816  
Keywords  
Abstract We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics.  
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 0162-8828 ISBN Medium  
Area Expedition Conference  
Notes CIC; 600.051; 600.052; 605.203 Approved no  
Call Number Admin @ si @ MVO2013 Serial 2289  
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Author Shida Beigpour edit  openurl
Title Illumination and object reflectance modeling Type Book Whole
Year (down) 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  
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Author Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga edit   pdf
doi  isbn
openurl 
Title Coloresia: An Interactive Colour Perception Device for the Visually Impaired Type Book Chapter
Year (down) 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 Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet edit   pdf
doi  openurl
Title Towards multispectral data acquisition with hand-held devices Type Conference Article
Year (down) 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  
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Author Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras edit   pdf
doi  openurl
Title Intrinsic Image Evaluation On Synthetic Complex Scenes Type Conference Article
Year (down) 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  
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Author Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat edit   pdf
doi  openurl
Title Discriminative Color Descriptors Type Conference Article
Year (down) 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  
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Author Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg edit   pdf
doi  isbn
openurl 
Title Evaluating the impact of color on texture recognition Type Conference Article
Year (down) 2013 Publication 15th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
Volume 8047 Issue Pages 154-162  
Keywords Color; Texture; image representation  
Abstract State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets.
 
Address York; UK; August 2013  
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 0302-9743 ISBN 978-3-642-40260-9 Medium  
Area Expedition Conference CAIP  
Notes CIC; 600.048 Approved no  
Call Number Admin @ si @ KWA2013 Serial 2263  
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Author Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier edit   pdf
openurl 
Title Automatic text localisation in scanned comic books Type Conference Article
Year (down) 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  
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Author Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier edit   pdf
doi  openurl
Title An active contour model for speech balloon detection in comics Type Conference Article
Year (down) 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  
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