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Author | Jordi Roca; A.Owen; G.Jordan; Y.Ling; C. Alejandro Parraga; A.Hurlbert |
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Title | Inter-individual Variations in Color Naming and the Structure of 3D Color Space | Type | Abstract | |||
Year | 2011 | Publication | Journal of Vision | Abbreviated Journal | VSS | |
Volume | 12 | Issue | 2 | Pages | 166 | |
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Abstract | 36.307
Many everyday behavioural uses of color vision depend on color naming ability, which is neither measured nor predicted by most standardized tests of color vision, for either normal or anomalous color vision. Here we demonstrate a new method to quantify color naming ability by deriving a compact computational description of individual 3D color spaces. Methods: Individual observers underwent standardized color vision diagnostic tests (including anomaloscope testing) and a series of custom-made color naming tasks using 500 distinct color samples, either CRT stimuli (“light”-based) or Munsell chips (“surface”-based), with both forced- and free-choice color naming paradigms. For each subject, we defined his/her color solid as the set of 3D convex hulls computed for each basic color category from the relevant collection of categorised points in perceptually uniform CIELAB space. From the parameters of the convex hulls, we derived several indices to characterise the 3D structure of the color solid and its inter-individual variations. Using a reference group of 25 normal trichromats (NT), we defined the degree of normality for the shape, location and overlap of each color region, and the extent of “light”-“surface” agreement. Results: Certain features of color perception emerge from analysis of the average NT color solid, e.g.: (1) the white category is slightly shifted towards blue; and (2) the variability in category border location across NT subjects is asymmetric across color space, with least variability in the blue/green region. Comparisons between individual and average NT indices reveal specific naming “deficits”, e.g.: (1) Category volumes for white, green, brown and grey are expanded for anomalous trichromats and dichromats; and (2) the focal structure of color space is disrupted more in protanopia than other forms of anomalous color vision. The indices both capture the structure of subjective color spaces and allow us to quantify inter-individual differences in color naming ability. |
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ISSN | 1534-7362 | ISBN | Medium | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ ROJ2011 | Serial | 1758 | |||
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Author | C. Alejandro Parraga; Jordi Roca; Maria Vanrell |
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Title | Do Basic Colors Influence Chromatic Adaptation? | Type | Journal Article | |||
Year | 2011 | Publication | Journal of Vision | Abbreviated Journal | VSS | |
Volume | 11 | Issue | 11 | Pages | 85 | |
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Abstract | Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered. | |||||
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ISSN | 1534-7362 | ISBN | Medium | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ PRV2011 | Serial | 1759 | |||
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Author | Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez |
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Title | Discriminative Compact Pyramids for Object and Scene Recognition | Type | Journal Article | |||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR | |
Volume | 45 | Issue | 4 | Pages | 1627-1636 | |
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Abstract | Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets. | |||||
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ISSN | 0031-3203 | ISBN | Medium | |||
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Notes | ISE; CAT;CIC | Approved | no | |||
Call Number | Admin @ si @ EKW2012 | Serial | 1807 | |||
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Author | Joost Van de Weijer; Shida Beigpour |
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Title | The Dichromatic Reflection Model: Future Research Directions and Applications | Type | Conference Article | |||
Year | 2011 | Publication | International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | dblp | |||||
Abstract | The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability. | |||||
Address | Algarve, Portugal | |||||
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Publisher | SciTePress | Place of Publication | Editor | Mestetskiy, Leonid and Braz, José | ||
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ISSN | ISBN | 978-989-8425-47-8 | Medium | |||
Area | Expedition | Conference | VISIGRAPP | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ WeB2011 | Serial | 1778 | |||
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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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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 | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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Title | Low-dimensional and Comprehensive Color Texture Description | Type | Journal Article | |||
Year | 2012 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU | |
Volume | 116 | Issue | I | Pages | 54-67 | |
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Abstract | Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are defined independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges).
A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent definition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz’s Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is defined from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap |
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ISSN | 1077-3142 | ISBN | Medium | |||
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Notes | CAT;CIC | Approved | no | |||
Call Number | Admin @ si @ ASV2012 | Serial | 1827 | |||
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Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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Title | Improving Color Constancy by Photometric Edge Weighting | Type | Journal Article | |||
Year | 2012 | Publication | IEEE Transaction on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI | |
Volume | 34 | Issue | 5 | Pages | 918-929 | |
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Abstract | : Edge-based color constancy methods make use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as material, shadow and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation. Therefore, in this paper, an extensive analysis is provided of different edge types on the performance of edge-based color constancy methods. First, an edge-based taxonomy is presented classifying edge types based on their photometric properties (e.g. material, shadow-geometry and highlights). Then, a performance evaluation of edge-based color constancy is provided using these different edge types. From this performance evaluation it is derived that specular and shadow edge types are more valuable than material edges for the estimation of the illuminant. To this end, the (iterative) weighted Grey-Edge algorithm is proposed in which these edge types are more emphasized for the estimation of the illuminant. Images that are recorded under controlled circumstances demonstrate that the proposed iterative weighted Grey-Edge algorithm based on highlights reduces the median angular error with approximately $25\%$. In an uncontrolled environment, improvements in angular error up to $11\%$ are obtained with respect to regular edge-based color constancy. | |||||
Address | Los Alamitos; CA; USA; | |||||
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ISSN | 0162-8828 | ISBN | Medium | |||
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Notes | CIC;ISE | Approved | no | |||
Call Number | Admin @ si @ GGW2012 | Serial | 1850 | |||
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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 | |||
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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 | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title | Modulating Shape Features by Color Attention for Object Recognition | Type | Journal Article | |||
Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV | |
Volume | 98 | Issue | 1 | Pages | 49-64 | |
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Abstract | Bag-of-words based image representation is a successful approach for object recognition. Generally, 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, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple 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, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information. | |||||
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Publisher | Springer Netherlands | Place of Publication | Editor | |||
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ISSN | 0920-5691 | ISBN | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ KWV2012 | Serial | 1864 | |||
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Author | Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell |
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Title | Portmanteau Vocabularies for Multi-Cue Image Representation | Type | Conference Article | |||
Year | 2011 | Publication | 25th Annual Conference on Neural Information Processing Systems | Abbreviated Journal | ||
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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 | |||||
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Area | Expedition | Conference | NIPS | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ KWB2011 | Serial | 1865 | |||
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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 | Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
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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 | |||
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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. | |||||
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Series Editor | Series Title | Perception 40 | Abbreviated Series Title | |||
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Area | Expedition | Conference | ECVP | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ RPV2011 | Serial | 1867 | |||
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Author | Joost Van de Weijer; Fahad Shahbaz Khan |
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Title | Fusing Color and Shape for Bag-of-Words Based Object Recognition | Type | Conference Article | |||
Year | 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 | |||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | |||
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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 |
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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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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Angel Sappa; Jordi Vitria | ||
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ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | ||
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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 |
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Title | Coloring Action Recognition in Still Images | Type | Journal Article | |||
Year | 2013 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV | |
Volume | 105 | Issue | 3 | Pages | 205-221 | |
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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. | |||||
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Publisher | Springer US | Place of Publication | Editor | |||
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ISSN | 0920-5691 | ISBN | Medium | |||
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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 |
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Title | Chromatic settings and the structural color constancy index | Type | Journal Article | |||
Year | 2013 | Publication | Journal of Vision | Abbreviated Journal | JV | |
Volume | 13 | Issue | 4-3 | Pages | 1-26 | |
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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. | |||||
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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 |
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Title | Low-level SpatioChromatic Grouping for Saliency Estimation | Type | Journal Article | |||
Year | 2013 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI | |
Volume | 35 | Issue | 11 | Pages | 2810-2816 | |
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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. | |||||
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ISSN | 0162-8828 | ISBN | Medium | |||
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Notes | CIC; 600.051; 600.052; 605.203 | Approved | no | |||
Call Number | Admin @ si @ MVO2013 | Serial | 2289 | |||
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Author | Javier Vazquez; J. Kevin O'Regan; Maria Vanrell; Graham D. Finlayson |
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Title | A new spectrally sharpened basis to predict colour naming, unique hues, and hue cancellation | Type | Journal Article | |||
Year | 2012 | Publication | Journal of Vision | Abbreviated Journal | VSS | |
Volume | 12 | Issue | 6 (7) | Pages | 1-14 | |
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Abstract | When light is reflected off a surface, there is a linear relation between the three human photoreceptor responses to the incoming light and the three photoreceptor responses to the reflected light. Different colored surfaces have different linear relations. Recently, Philipona and O'Regan (2006) showed that when this relation is singular in a mathematical sense, then the surface is perceived as having a highly nameable color. Furthermore, white light reflected by that surface is perceived as corresponding precisely to one of the four psychophysically measured unique hues. However, Philipona and O'Regan's approach seems unrelated to classical psychophysical models of color constancy. In this paper we make this link. We begin by transforming cone sensors to spectrally sharpened counterparts. In sharp color space, illumination change can be modeled by simple von Kries type scalings of response values within each of the spectrally sharpened response channels. In this space, Philipona and O'Regan's linear relation is captured by a simple Land-type color designator defined by dividing reflected light by incident light. This link between Philipona and O'Regan's theory and Land's notion of color designator gives the model biological plausibility. We then show that Philipona and O'Regan's singular surfaces are surfaces which are very close to activating only one or only two of such newly defined spectrally sharpened sensors, instead of the usual three. Closeness to zero is quantified in a new simplified measure of singularity which is also shown to relate to the chromaticness of colors. As in Philipona and O'Regan's original work, our new theory accounts for a large variety of psychophysical color data. | |||||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ VOV2012 | Serial | 1998 | |||
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