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Author | Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus |
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Title | Color Naming | Type | Book Chapter | |||
Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | ||
Volume | Issue | 17 | Pages | 287-317 | ||
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Publisher | John Wiley & Sons, Ltd. | Place of Publication | Editor | Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek | ||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ WBV2012 | Serial | 2063 | |||
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Author | Javier Vazquez; Maria Vanrell; Robert Benavente |
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Title | Color names as a constraint for Computer Vision problems | Type | Conference Article | |||
Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | ||
Volume | Issue | Pages | 324–328 | |||
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Abstract | Computer Vision Problems are usually ill-posed. Constraining de gamut of possible solutions is then a necessary step. Many constrains for different problems have been developed during years. In this paper, we present a different way of constraining some of these problems: the use of color names. In particular, we will focus on segmentation, representation ans constancy. | |||||
Address | Gjovik (Norway) | |||||
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Area | Expedition | Conference | CREATE | |||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ VVB2010 | Serial | 1328 | |||
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Author | Ivet Rafegas |
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Title | Color in Visual Recognition: from flat to deep representations and some biological parallelisms | Type | Book Whole | |||
Year | 2017 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Visual recognition is one of the main problems in computer vision that attempts to solve image understanding by deciding what objects are in images. This problem can be computationally solved by using relevant sets of visual features, such as edges, corners, color or more complex object parts. This thesis contributes to how color features have to be represented for recognition tasks.
Image features can be extracted following two different approaches. A first approach is defining handcrafted descriptors of images which is then followed by a learning scheme to classify the content (named flat schemes in Kruger et al. (2013). In this approach, perceptual considerations are habitually used to define efficient color features. Here we propose a new flat color descriptor based on the extension of color channels to boost the representation of spatio-chromatic contrast that surpasses state-of-the-art approaches. However, flat schemes present a lack of generality far away from the capabilities of biological systems. A second approach proposes evolving these flat schemes into a hierarchical process, like in the visual cortex. This includes an automatic process to learn optimal features. These deep schemes, and more specifically Convolutional Neural Networks (CNNs), have shown an impressive performance to solve various vision problems. However, there is a lack of understanding about the internal representation obtained, as a result of automatic learning. In this thesis we propose a new methodology to explore the internal representation of trained CNNs by defining the Neuron Feature as a visualization of the intrinsic features encoded in each individual neuron. Additionally, and inspired by physiological techniques, we propose to compute different neuron selectivity indexes (e.g., color, class, orientation or symmetry, amongst others) to label and classify the full CNN neuron population to understand learned representations. Finally, using the proposed methodology, we show an in-depth study on how color is represented on a specific CNN, trained for object recognition, that competes with primate representational abilities (Cadieu et al (2014)). We found several parallelisms with biological visual systems: (a) a significant number of color selectivity neurons throughout all the layers; (b) an opponent and low frequency representation of color oriented edges and a higher sampling of frequency selectivity in brightness than in color in 1st layer like in V1; (c) a higher sampling of color hue in the second layer aligned to observed hue maps in V2; (d) a strong color and shape entanglement in all layers from basic features in shallower layers (V1 and V2) to object and background shapes in deeper layers (V4 and IT); and (e) a strong correlation between neuron color selectivities and color dataset bias. |
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Address | November 2017 | |||||
Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell | ||
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ISSN | ISBN | 978-84-945373-7-0 | Medium | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Raf2017 | Serial | 3100 | |||
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Author | Ramon Baldrich; Maria Vanrell; Robert Benavente; Anna Salvatella |
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Title | Color Enhancement based on perceptual sharpening | Type | Miscellaneous | |||
Year | 2003 | Publication | Proceedings of the IEEE International Conference on Image Processing | Abbreviated Journal | ||
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Address | Barcelona | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ BVB2003 | Serial | 370 | |||
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Author | Ivet Rafegas; Maria Vanrell |
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Title | Color encoding in biologically-inspired convolutional neural networks | Type | Journal Article | |||
Year | 2018 | Publication | Vision Research | Abbreviated Journal | VR | |
Volume | 151 | Issue | Pages | 7-17 | ||
Keywords | Color coding; Computer vision; Deep learning; Convolutional neural networks | |||||
Abstract | Convolutional Neural Networks have been proposed as suitable frameworks to model biological vision. Some of these artificial networks showed representational properties that rival primate performances in object recognition. In this paper we explore how color is encoded in a trained artificial network. It is performed by estimating a color selectivity index for each neuron, which allows us to describe the neuron activity to a color input stimuli. The index allows us to classify whether they are color selective or not and if they are of a single or double color. We have determined that all five convolutional layers of the network have a large number of color selective neurons. Color opponency clearly emerges in the first layer, presenting 4 main axes (Black-White, Red-Cyan, Blue-Yellow and Magenta-Green), but this is reduced and rotated as we go deeper into the network. In layer 2 we find a denser hue sampling of color neurons and opponency is reduced almost to one new main axis, the Bluish-Orangish coinciding with the dataset bias. In layers 3, 4 and 5 color neurons are similar amongst themselves, presenting different type of neurons that detect specific colored objects (e.g., orangish faces), specific surrounds (e.g., blue sky) or specific colored or contrasted object-surround configurations (e.g. blue blob in a green surround). Overall, our work concludes that color and shape representation are successively entangled through all the layers of the studied network, revealing certain parallelisms with the reported evidences in primate brains that can provide useful insight into intermediate hierarchical spatio-chromatic representations. | |||||
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Notes | CIC; 600.051; 600.087 | Approved | no | |||
Call Number | Admin @ si @RaV2018 | Serial | 3114 | |||
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Author | Javier Vazquez; Maria Vanrell; Ramon Baldrich; Francesc Tous |
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Title | Color Constancy by Category Correlation | Type | Journal Article | |||
Year | 2012 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
Volume | 21 | Issue | 4 | Pages | 1997-2007 | |
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Abstract | Finding color representations which are stable to illuminant changes is still an open problem in computer vision. Until now most approaches have been based on physical constraints or statistical assumptions derived from the scene, while very little attention has been paid to the effects that selected illuminants have
on the final color image representation. The novelty of this work is to propose perceptual constraints that are computed on the corrected images. We define the category hypothesis, which weights the set of feasible illuminants according to their ability to map the corrected image onto specific colors. Here we choose these colors as the universal color categories related to basic linguistic terms which have been psychophysically measured. These color categories encode natural color statistics, and their relevance across different cultures is indicated by the fact that they have received a common color name. From this category hypothesis we propose a fast implementation that allows the sampling of a large set of illuminants. Experiments prove that our method rivals current state-of-art performance without the need for training algorithmic parameters. Additionally, the method can be used as a framework to insert top-down information from other sources, thus opening further research directions in solving for color constancy. |
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ISSN | 1057-7149 | ISBN | Medium | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ VVB2012 | Serial | 1999 | |||
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Author | Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich |
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Title | Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset | Type | Journal Article | |||
Year | 2009 | Publication | Journal of Imaging Science and Technology | Abbreviated Journal | ||
Volume | 53 | Issue | 3 | Pages | 031105–9 | |
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Abstract | The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene. | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ VPV2009a | Serial | 1171 | |||
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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 | 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 | Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo |
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Title | Chromatic induction and contrast masking: similar models, different goals? | Type | Conference Article | |||
Year | 2013 | Publication | Human Vision and Electronic Imaging XVIII | Abbreviated Journal | ||
Volume | 8651 | Issue | Pages | |||
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Abstract | Normalization of signals coming from linear sensors is an ubiquitous mechanism of neural adaptation.1 Local interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical facts including (1) masking of spatial patterns, (2) non-linearities of motion sensors, (3) adaptation of color perception, (4) brightness and chromatic induction, and (5) image quality assessment. Although the above models have formal and qualitative similarities, it does not necessarily mean that the mechanisms involved are pursuing the same statistical goal. For instance, in the case of chromatic mechanisms (disregarding spatial information), different parameters in the normalization give rise to optimal discrimination or adaptation, and different non-linearities may give rise to error minimization or component independence. In the case of spatial sensors (disregarding color information), a number of studies have pointed out the benefits of masking in statistical independence terms. However, such statistical analysis has not been performed for spatio-chromatic induction models where chromatic perception depends on spatial configuration. In this work we investigate whether successful spatio-chromatic induction models,6 increase component independence similarly as previously reported for masking models. Mutual information analysis suggests that seeking an efficient chromatic representation may explain the prevalence of induction effects in spatially simple images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. | |||||
Address | San Francisco CA; USA; February 2013 | |||||
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Area | Expedition | Conference | HVEI | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ JOL2013 | Serial | 2240 | |||
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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 | Enric Marti; Jordi Rocarias; Ricardo Toledo |
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Title | Caront: gestió flexible de grups d’alumnes en una asignatura i activitats sobre grups. Nova activitat de control | Type | Miscellaneous | |||
Year | 2008 | Publication | V Jornades d’Innovació Docent | Abbreviated Journal | ||
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Notes | IAM;RV;CIC;ADAS | Approved | no | |||
Call Number | IAM @ iam @ MRT2008a | Serial | 1617 | |||
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Author | Danna Xue; Luis Herranz; Javier Vazquez; Yanning Zhang |
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Title | Burst Perception-Distortion Tradeoff: Analysis and Evaluation | Type | Conference Article | |||
Year | 2023 | Publication | IEEE International Conference on Acoustics, Speech and Signal Processing | Abbreviated Journal | ||
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Abstract | Burst image restoration attempts to effectively utilize the complementary cues appearing in sequential images to produce a high-quality image. Most current methods use all the available images to obtain the reconstructed image. However, using more images for burst restoration is not always the best option regarding reconstruction quality and efficiency, as the images acquired by handheld imaging devices suffer from degradation and misalignment caused by the camera noise and shake. In this paper, we extend the perception-distortion tradeoff theory by introducing multiple-frame information. We propose the area of the unattainable region as a new metric for perception-distortion tradeoff evaluation and comparison. Based on this metric, we analyse the performance of burst restoration from the perspective of the perception-distortion tradeoff under both aligned bursts and misaligned bursts situations. Our analysis reveals the importance of inter-frame alignment for burst restoration and shows that the optimal burst length for the restoration model depends both on the degree of degradation and misalignment. | |||||
Address | Rodhes Islands; Greece; June 2023 | |||||
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Area | Expedition | Conference | ICASSP | |||
Notes | CIC; MACO | Approved | no | |||
Call Number | Admin @ si @ XHV2023 | Serial | 3909 | |||
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Author | Xavier Otazu; Maria Vanrell |
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Title | Building Perceived Colour Images. | Type | Miscellaneous | |||
Year | 2004 | Publication | CGIV 2004 Second European Conference on Colour in Graphics, Imaging, and Vision, 140:145 | Abbreviated Journal | ||
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Address | Aachen (Germany) | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ OtV2004 | Serial | 450 | |||
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Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco |
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Title | Brightness induction by contextual influences in V1: a neurodynamical account | Type | Abstract | |||
Year | 2012 | Publication | Journal of Vision | Abbreviated Journal | VSS | |
Volume | 12 | Issue | 9 | Pages | ||
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Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas and reveals fundamental properties of neural organization in the visual system. Several phenomenological models have been proposed that successfully account for psychophysical data (Pessoa et al. 1995, Blakeslee and McCourt 2004, Barkan et al. 2008, Otazu et al. 2008).
Neurophysiological evidence suggests that brightness information is explicitly represented in V1 and neuronal response modulations have been observed followingluminance changes outside their receptive fields (Rossi and Paradiso, 1999). In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (1999) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2–3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant effect of contextual influences. In our model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition which makes it possible to recover an image reflecting the perceived intensity. The proposed model successfully accounts for well known pyschophysical effects (among them: the White's and modified White's effects, the Todorović, Chevreul, achromatic ring patterns, and grating induction effects). Our work suggests that intra-cortical interactions in the primary visual cortex could partially explain perceptual brightness induction effects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual pathway. |
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Call Number | Admin @ si @ OPD2012b | Serial | 2178 | |||
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Author | Bojana Gajic; Ariel Amato; Ramon Baldrich; Carlo Gatta |
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Title | Bag of Negatives for Siamese Architectures | Type | Conference Article | |||
Year | 2019 | Publication | 30th British Machine Vision Conference | Abbreviated Journal | ||
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Abstract | Training a Siamese architecture for re-identification with a large number of identities is a challenging task due to the difficulty of finding relevant negative samples efficiently. In this work we present Bag of Negatives (BoN), a method for accelerated and improved training of Siamese networks that scales well on datasets with a very large number of identities. BoN is an efficient and loss-independent method, able to select a bag of high quality negatives, based on a novel online hashing strategy. | |||||
Address | Cardiff; United Kingdom; September 2019 | |||||
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Area | Expedition | Conference | BMVC | |||
Notes | CIC; 600.140; 600.118 | Approved | no | |||
Call Number | Admin @ si @ GAB2019b | Serial | 3263 | |||
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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 | |||
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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 | Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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Title | Automatic text localisation in scanned comic books | Type | Conference Article | |||
Year | 2013 | Publication | Proceedings of the International Conference on Computer Vision Theory and Applications | Abbreviated Journal | ||
Volume | Issue | Pages | 814-819 | |||
Keywords | Text localization; comics; text/graphic separation; complex background; unstructured document | |||||
Abstract | Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented. | |||||
Address | Barcelona; February 2013 | |||||
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Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | VISAPP | |||
Notes | DAG; CIC; 600.056 | Approved | no | |||
Call Number | Admin @ si @ RKW2013b | Serial | 2261 | |||
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