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Author | David Augusto Rojas |
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Title | Colouring Local Feature Detection for Matching | Type | Report | |||
Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
Volume | 133 | Issue | Pages | |||
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Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
Publisher | Place of Publication | Bellaterra, Barcelona | Editor | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Roj2009 | Serial | 2392 | |||
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Author | Domicele Jonauskaite; Lucia Camenzind; C. Alejandro Parraga; Cecile N Diouf; Mathieu Mercapide Ducommun; Lauriane Müller; Melanie Norberg; Christine Mohr |
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Title | Colour-emotion associations in individuals with red-green colour blindness | Type | Journal Article | |||
Year | 2021 | Publication | PeerJ | Abbreviated Journal | ||
Volume | 9 | Issue | Pages | e11180 | ||
Keywords | Affect; Chromotherapy; Colour cognition; Colour vision deficiency; Cross-modal correspondences; Daltonism; Deuteranopia; Dichromatic; Emotion; Protanopia. | |||||
Abstract | Colours and emotions are associated in languages and traditions. Some of us may convey sadness by saying feeling blue or by wearing black clothes at funerals. The first example is a conceptual experience of colour and the second example is an immediate perceptual experience of colour. To investigate whether one or the other type of experience more strongly drives colour-emotion associations, we tested 64 congenitally red-green colour-blind men and 66 non-colour-blind men. All participants associated 12 colours, presented as terms or patches, with 20 emotion concepts, and rated intensities of the associated emotions. We found that colour-blind and non-colour-blind men associated similar emotions with colours, irrespective of whether colours were conveyed via terms (r = .82) or patches (r = .80). The colour-emotion associations and the emotion intensities were not modulated by participants' severity of colour blindness. Hinting at some additional, although minor, role of actual colour perception, the consistencies in associations for colour terms and patches were higher in non-colour-blind than colour-blind men. Together, these results suggest that colour-emotion associations in adults do not require immediate perceptual colour experiences, as conceptual experiences are sufficient. | |||||
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Notes | CIC; LAMP; 600.120; 600.128 | Approved | no | |||
Call Number | Admin @ si @ JCP2021 | Serial | 3564 | |||
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Author | Ivet Rafegas; Maria Vanrell |
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Title | Colour Visual Coding in trained Deep Neural Networks | Type | Abstract | |||
Year | 2016 | Publication | European Conference on Visual Perception | Abbreviated Journal | ||
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Address | Barcelona; Spain; August 2016 | |||||
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Area | Expedition | Conference | ECVP | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ RaV2016b | Serial | 2895 | |||
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Author | Robert Benavente; M.C. Olive; Maria Vanrell; Ramon Baldrich |
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Title | Colour Perception: A Simple Method for Colour Naming. | Type | Miscellaneous | |||
Year | 1999 | Publication | Abbreviated Journal | |||
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Address | Girona | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ BOV1999 | Serial | 47 | |||
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Author | Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva |
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Title | Colour Normalisation Based on Background Information. | Type | Miscellaneous | |||
Year | 2001 | Publication | Proceeding ICIP 2001, IEEE International Conference on Image Processing | Abbreviated Journal | ICIP 2001 | |
Volume | Issue | 1 | Pages | 874–877 | ||
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Address | Grecia. | |||||
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Notes | ADAS;DAG;CIC | Approved | no | |||
Call Number | ADAS @ adas @ VLP2001 | Serial | 167 | |||
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Author | Robert Benavente; Ramon Baldrich; M.C. Olive; Maria Vanrell |
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Title | Colour Naming Considering the Colour Variability Problem. | Type | Miscellaneous | |||
Year | 2000 | Publication | Computacion y Sistemas, 4(1):30–43. | Abbreviated Journal | ||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ BBO2000 | Serial | 242 | |||
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Author | Xavier Otazu; Maria Vanrell; C. Alejandro Parraga |
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Title | Colour induction effects are modelled by a low-level multiresolution wavelet framework | Type | Journal | |||
Year | 2008 | Publication | Perception 37(Suppl.): 107 | Abbreviated Journal | ||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ OVP2008b | Serial | 1055 | |||
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Author | Eduard Vazquez; Ramon Baldrich |
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Title | Colour Image Segmentation in Presence of Shadows | Type | Conference Article | |||
Year | 2008 | Publication | 4th European Conference on Colour in Graphics, Imaging and Vision Proceedings | Abbreviated Journal | ||
Volume | Issue | Pages | 383–387 | |||
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Address | Terrassa (Spain) | |||||
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Area | Expedition | Conference | CGIV08 | |||
Notes | CAT;CIC | Approved | no | |||
Call Number | CAT @ cat @ VaB2008 | Serial | 966 | |||
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Author | Javier Vazquez |
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Title | Colour Constancy in Natural Through Colour Naming and Sensor Sharpening | Type | Book Whole | |||
Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.
To deal with the illuminant selection step, we hypothesise that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to the way that the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation. The implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant change. Consequently, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimised to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimise different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D. Several research lines still remain open. One natural extension would be to measure the effects of using the computed sharp sensors on the category hypothesis, while another might be to insert spatial contextual information to improve category hypothesis. Finally, much work still needs to be done to explore how individual sensors can be adjusted to the colours in a scene. |
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell;Graham D. Finlayson | ||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Vaz2011a | Serial | 1785 | |||
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Author | Robert Benavente; C. Alejandro Parraga; Maria Vanrell |
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Title | Colour categories boundaries are better defined in contextual conditions | Type | Journal Article | |||
Year | 2009 | Publication | Perception | Abbreviated Journal | PER | |
Volume | 38 | Issue | Pages | 36 | ||
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Abstract | In a previous experiment [Parraga et al, 2009 Journal of Imaging Science and Technology 53(3)] the boundaries between basic colour categories were measured by asking subjects to categorize colour samples presented in isolation (ie on a dark background) using a YES/NO paradigm. Results showed that some boundaries (eg green – blue) were very diffuse and the subjects' answers presented bimodal distributions, which were attributed to the emergence of non-basic categories in those regions (eg turquoise). To confirm these results we performed a new experiment focussed on the boundaries where bimodal distributions were more evident. In this new experiment rectangular colour samples were presented surrounded by random colour patches to simulate contextual conditions on a calibrated CRT monitor. The names of two neighbouring colours were shown at the bottom of the screen and subjects selected the boundary between these colours by controlling the chromaticity of the central patch, sliding it across these categories' frontier. Results show that in this new experimental paradigm, the formerly uncertain inter-colour category boundaries are better defined and the dispersions (ie the bimodal distributions) that occurred in the previous experiment disappear. These results may provide further support to Berlin and Kay's basic colour terms theory. | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ BPV2009 | Serial | 1192 | |||
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Author | Fahad Shahbaz Khan |
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Title | Coloring bag-of-words based image representations | Type | Book Whole | |||
Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Put succinctly, the bag-of-words based image representation is the most successful approach for object and scene recognition. Within the bag-of-words framework the optimal fusion of multiple cues, such as shape, texture and color, still remains an active research domain. There exist two main approaches to combine color and shape information within the bag-of-words framework. The first approach called, early fusion, fuses color and shape at the feature level as a result of which a joint colorshape vocabulary is produced. The second approach, called late fusion, concatenates histogram representation of both color and shape, obtained independently. In the first part of this thesis, we analyze the theoretical implications of both early and late feature fusion. We demonstrate that both these approaches are suboptimal for a subset of object categories. Consequently, we propose a novel method for recognizing object categories when using multiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom-up and top-down attention maps. Subsequently, the color attention maps are used to modulate the weights of the shape features. Shape features are given more weight in regions with higher attention and vice versa. The approach is tested on several benchmark object recognition data sets and the results clearly demonstrate the effectiveness of our proposed method. In the second part of the thesis, we investigate the problem of obtaining compact spatial pyramid representations for object and scene recognition. Spatial pyramids have been successfully applied to incorporate spatial information into bag-of-words based image representation. However, a major drawback of spatial pyramids is that it leads to high dimensional image representations. We present a novel framework for obtaining compact pyramid representation. The approach reduces the size of a high dimensional pyramid representation upto an order of magnitude without any significant reduction in accuracy. Moreover, we also investigate the optimal combination of multiple features such as color and shape within the context of our compact pyramid representation. Finally, we describe a novel technique to build discriminative visual words from multiple cues learned independently from training images. To this end, we use an information theoretic vocabulary compression technique to find discriminative combinations of visual cues and the resulting visual vocabulary is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. The approach is tested on standard object recognition data sets. The results obtained clearly demonstrate the effectiveness of our approach. | |||||
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Place of Publication | Editor | Joost Van de Weijer;Maria Vanrell | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Kha2011 | Serial | 1838 | |||
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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 | 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 | ||
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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. | |||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | |||
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ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | ||
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Notes | CIC; 600.052; 605.203 | Approved | no | |||
Call Number | Admin @ si @ GBP2013 | Serial | 2266 | |||
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Author | Hassan Ahmed Sial; S. Sancho; Ramon Baldrich; Robert Benavente; Maria Vanrell |
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Title | Color-based data augmentation for Reflectance Estimation | Type | Conference Article | |||
Year | 2018 | Publication | 26th Color Imaging Conference | Abbreviated Journal | ||
Volume | Issue | Pages | 284-289 | |||
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Abstract | Deep convolutional architectures have shown to be successful frameworks to solve generic computer vision problems. The estimation of intrinsic reflectance from single image is not a solved problem yet. Encoder-Decoder architectures are a perfect approach for pixel-wise reflectance estimation, although it usually suffers from the lack of large datasets. Lack of data can be partially solved with data augmentation, however usual techniques focus on geometric changes which does not help for reflectance estimation. In this paper we propose a color-based data augmentation technique that extends the training data by increasing the variability of chromaticity. Rotation on the red-green blue-yellow plane of an opponent space enable to increase the training set in a coherent and sound way that improves network generalization capability for reflectance estimation. We perform some experiments on the Sintel dataset showing that our color-based augmentation increase performance and overcomes one of the state-of-the-art methods. | |||||
Address | Vancouver; November 2018 | |||||
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Area | Expedition | Conference | CIC | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ SSB2018a | Serial | 3129 | |||
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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 | ||
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ISSN | ISBN | 978-1-4614-7320-6 | Medium | |||
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Notes | CIC; 600.074 | Approved | no | |||
Call Number | Admin @ si @ Par2014 | Serial | 2512 | |||
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Author | Felipe Lumbreras; Joan Serrat; Ramon Baldrich; Maria Vanrell; Juan J. Villanueva |
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Title | Color Texture Recognition Through Multiresolution Features | Type | Miscellaneous | |||
Year | 2001 | Publication | QCAV 2001 International Conference on Quality Control by Artificial Vision, France, 1:114–121. | Abbreviated Journal | ||
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Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ LSB2001 | Serial | 124 | |||
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Author | Ivet Rafegas; Maria Vanrell |
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Title | Color spaces emerging from deep convolutional networks | Type | Conference Article | |||
Year | 2016 | Publication | 24th Color and Imaging Conference | Abbreviated Journal | ||
Volume | Issue | Pages | 225-230 | |||
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Abstract | Award for the best interactive session
Defining color spaces that provide a good encoding of spatio-chromatic properties of color surfaces is an open problem in color science [8, 22]. Related to this, in computer vision the fusion of color with local image features has been studied and evaluated [16]. In human vision research, the cells which are selective to specific color hues along the visual pathway are also a focus of attention [7, 14]. In line with these research aims, in this paper we study how color is encoded in a deep Convolutional Neural Network (CNN) that has been trained on more than one million natural images for object recognition. These convolutional nets achieve impressive performance in computer vision, and rival the representations in human brain. In this paper we explore how color is represented in a CNN architecture that can give some intuition about efficient spatio-chromatic representations. In convolutional layers the activation of a neuron is related to a spatial filter, that combines spatio-chromatic representations. We use an inverted version of it to explore the properties. Using a series of unsupervised methods we classify different type of neurons depending on the color axes they define and we propose an index of color-selectivity of a neuron. We estimate the main color axes that emerge from this trained net and we prove that colorselectivity of neurons decreases from early to deeper layers. |
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Address | San Diego; USA; November 2016 | |||||
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Area | Expedition | Conference | CIC | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ RaV2016a | Serial | 2894 | |||
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Author | Ivet Rafegas; Maria Vanrell |
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Title | Color representation in CNNs: parallelisms with biological vision | Type | Conference Article | |||
Year | 2017 | Publication | ICCV Workshop on Mutual Benefits ofr Cognitive and Computer Vision | Abbreviated Journal | ||
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Abstract | Convolutional Neural Networks (CNNs) trained for object recognition tasks present representational capabilities approaching to primate visual systems [1]. This provides a computational framework to explore how image features
are efficiently represented. Here, we dissect a trained CNN [2] to study how color is represented. We use a classical methodology used in physiology that is measuring index of selectivity of individual neurons to specific features. We use ImageNet Dataset [20] images and synthetic versions of them to quantify color tuning properties of artificial neurons to provide a classification of the network population. We conclude three main levels of color representation showing some parallelisms with biological visual systems: (a) a decomposition in a circular hue space to represent single color regions with a wider hue sampling beyond the first layer (V2), (b) the emergence of opponent low-dimensional spaces in early stages to represent color edges (V1); and (c) a strong entanglement between color and shape patterns representing object-parts (e.g. wheel of a car), objectshapes (e.g. faces) or object-surrounds configurations (e.g. blue sky surrounding an object) in deeper layers (V4 or IT). |
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Address | Venice; Italy; October 2017 | |||||
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Area | Expedition | Conference | ICCV-MBCC | |||
Notes | CIC; 600.087; 600.051 | Approved | no | |||
Call Number | Admin @ si @ RaV2017 | Serial | 2984 | |||
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