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| Author | Anna Salvatella; Maria Vanrell; Juan J. Villanueva |
 
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| Title | Texture Description based on Subtexture Components, 3rd International Workshop on Texture Syntesis and Analysis | Type | Conference Article | |||
| Year | 2003 | Publication | 3rd International Workshop on Texture Synthesis and Analysis, | Abbreviated Journal | ||
| Volume | Issue | Pages | 77–82 | |||
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| Address | Nice | |||||
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1-904410-11-1 | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ SVV2003 | Serial | 422 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
 
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| 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 | |||
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| 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 | |||||
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| Language | Summary Language | Original Title | ||||
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| 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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| Author | Josep M. Gonfaus; Xavier Boix; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez |
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| Title | Harmony Potentials for Joint Classification and Segmentation | Type | Conference Article | |||
| Year | 2010 | Publication | 23rd IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 3280–3287 | |||
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| Abstract | Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales. However, these models do not allow multiple labels to be assigned to a single node. At higher scales in the image, this yields an oversimplified model, since multiple classes can be reasonable expected to appear within one region. This simplified model especially limits the impact that observations at larger scales may have on the CRF model. Neglecting the information at larger scales is undesirable since class-label estimates based on these scales are more reliable than at smaller, noisier scales. To address this problem, we propose a new potential, called harmony potential, which can encode any possible combination of class labels. We propose an effective sampling strategy that renders tractable the underlying optimization problem. Results show that our approach obtains state-of-the-art results on two challenging datasets: Pascal VOC 2009 and MSRC-21. | |||||
| Address | San Francisco CA, USA | |||||
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| Language | Summary Language | Original Title | ||||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1063-6919 | ISBN |
978-1-4244-6984-0 | Medium | ||
| Area | Expedition | Conference | CVPR | |||
| Notes | ADAS;CIC;ISE | Approved | no | |||
| Call Number | ADAS @ adas @ GBW2010 | Serial | 1296 | |||
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| Author | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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| 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 | |||
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| 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) | |||||
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| Language | Summary Language | Original Title | ||||
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| 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 | Naila Murray; Sandra Skaff; Luca Marchesotti; Florent Perronnin |
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| 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. | |||||
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| Publisher | ACM Press | Place of Publication | Editor | |||
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| ISSN | ISBN |
978-1-4503-0907-3 | Medium | |||
| Area | Expedition | Conference | NPAR | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ MSM2011 | Serial | 1866 | |||
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| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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| 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 | |||||
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| Language | Summary Language | Original Title | ||||
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| 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 | Shida Beigpour; Joost Van de Weijer |
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| Title | Object Recoloring Based on Intrinsic Image Estimation | Type | Conference Article | |||
| Year | 2011 | Publication | 13th IEEE International Conference in Computer Vision | Abbreviated Journal | ||
| Volume | Issue | Pages | 327 - 334 | |||
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| Abstract | Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods. | |||||
| Address | Barcelona | |||||
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| Language | Summary Language | Original Title | ||||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1550-5499 | ISBN |
978-1-4577-1101-5 | Medium | ||
| Area | Expedition | Conference | ICCV | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ BeW2011 | Serial | 1781 | |||
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| Author | C. Alejandro Parraga |
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| Title | Color Vision, Computational Methods for | Type | Book Chapter | |||
| Year | 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. | |||||
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| Publisher | Springer-Verlag Berlin Heidelberg | Place of Publication | Editor | Dieter Jaeger; Ranu Jung | ||
| Language | Summary Language | Original Title | ||||
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| 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 | Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez |
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| 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. |
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| Address | Providence; Rhode Island; USA; | |||||
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| 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 | Naila Murray; Luca Marchesotti; Florent Perronnin |
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| 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 | |||
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| 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 | |||||
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| 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 | |||
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| Author | Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
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| 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 | |||
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| 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 | |||||
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| 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 | Jaime Moreno; Xavier Otazu |
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| Title | Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder | Type | Conference Article | |||
| Year | 2011 | Publication | IEEE International Conference on Multimedia and Expo | Abbreviated Journal | ||
| Volume | Issue | Pages | 1-6 | |||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder. | |||||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1945-7871 | ISBN |
978-1-61284-348-3 | Medium | ||
| Area | Expedition | Conference | ICME | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ MoO2011a | Serial | 2176 | |||
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| Author | Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
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| 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. | |||||
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| 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 | C. Alejandro Parraga |
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| Title | Perceptual Psychophysics | Type | Book Chapter | |||
| Year | 2015 | Publication | Biologically-Inspired Computer Vision: Fundamentals and Applications | Abbreviated Journal | ||
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| Publisher | Place of Publication | Editor | G.Cristobal; M.Keil; L.Perrinet | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN |
978-3-527-41264-8 | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC; 600.074 | Approved | no | |||
| Call Number | Admin @ si @ Par2015 | Serial | 2600 | |||
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| Author | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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| 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 | ||
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| 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. | |||||
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| 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 | Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich |
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| 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 | |||||
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| 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 | |||
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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 | Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana |
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| Title | Interactive Visual and Semantic Image Retrieval | Type | Book Chapter | |||
| Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | ||
| Volume | 48 | Issue | Pages | 31-35 | ||
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| 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. | |||||
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| 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 | |||
| Permanent link to this record | ||||||
| Author | Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga |
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| 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 | |||
| Permanent link to this record | ||||||