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| Author | Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras |
 
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| Title | Intrinsic Image Evaluation On Synthetic Complex Scenes | Type  |
Conference Article | |||
| Year | 2013 | Publication | 20th IEEE International Conference on Image Processing | Abbreviated Journal | ||
| Volume | Issue | Pages | 285 - 289 | |||
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| Abstract | Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth
procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes. |
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| Address | Melbourne; Australia; September 2013 | |||||
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| Area | Expedition | Conference | ICIP | |||
| Notes | CIC; 600.048; 600.052; 600.051 | Approved | no | |||
| Call Number | Admin @ si @ BSW2013 | Serial | 2264 | |||
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| Author | Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat |
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| Title | Discriminative Color Descriptors | Type |
Conference Article | |||
| Year | 2013 | Publication | IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 2866 - 2873 | |||
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| Abstract | Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200. | |||||
| Address | Portland; Oregon; June 2013 | |||||
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| Language | Summary Language | Original Title | ||||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1063-6919 | ISBN | Medium | |||
| Area | Expedition | Conference | CVPR | |||
| Notes | CIC; 600.048 | Approved | no | |||
| Call Number | Admin @ si @ KWK2013a | Serial | 2262 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg |
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| Title | Evaluating the impact of color on texture recognition | Type |
Conference Article | |||
| Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | ||
| Volume | 8047 | Issue | Pages | 154-162 | ||
| Keywords | Color; Texture; image representation | |||||
| Abstract | State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets. |
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| Address | York; UK; August 2013 | |||||
| Corporate Author | Thesis | |||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | ||||
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| ISSN | 0302-9743 | ISBN | 978-3-642-40260-9 | Medium | ||
| Area | Expedition | Conference | CAIP | |||
| Notes | CIC; 600.048 | Approved | no | |||
| Call Number | Admin @ si @ KWA2013 | Serial | 2263 | |||
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| Author | Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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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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| Area | Expedition | Conference | VISAPP | |||
| Notes | DAG; CIC; 600.056 | Approved | no | |||
| Call Number | Admin @ si @ RKW2013b | Serial | 2261 | |||
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| Author | Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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| Title | An active contour model for speech balloon detection in comics | Type |
Conference Article | |||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 1240-1244 | |||
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| Abstract | Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented. | |||||
| Address | washington; USA; August 2013 | |||||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1520-5363 | ISBN | Medium | |||
| Area | Expedition | Conference | ICDAR | |||
| Notes | DAG; CIC; 600.056 | Approved | no | |||
| Call Number | Admin @ si @ RKW2013a | Serial | 2260 | |||
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| Author | Alicia Fornes; Xavier Otazu; Josep Llados |
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| Title | Show through cancellation and image enhancement by multiresolution contrast processing | Type |
Conference Article | |||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 200-204 | |||
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| Abstract | Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities. | |||||
| Address | Washington; USA; August 2013 | |||||
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| ISSN | 1520-5363 | ISBN | Medium | |||
| Area | Expedition | Conference | ICDAR | |||
| Notes | DAG; 602.006; 600.045; 600.061; 600.052;CIC | Approved | no | |||
| Call Number | Admin @ si @ FOL2013 | Serial | 2241 | |||
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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 | Javier Vazquez; Robert Benavente; Maria Vanrell |
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| Title | Naming constraints constancy | Type |
Conference Article | |||
| Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | ||
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| Abstract | Different studies have shown that languages from industrialized cultures
share a set of 11 basic colour terms: red, green, blue, yellow, pink, purple, brown, orange, black, white, and grey (Berlin & Kay, 1969, Basic Color Terms, University of California Press)( Kay & Regier, 2003, PNAS, 100, 9085-9089). Some of these studies have also reported the best representatives or focal values of each colour (Boynton and Olson, 1990, Vision Res. 30,1311–1317), (Sturges and Whitfield, 1995, CRA, 20:6, 364–376). Some further studies have provided us with fuzzy datasets for color naming by asking human observers to rate colours in terms of membership values (Benavente -et al-, 2006, CRA. 31:1, 48–56,). Recently, a computational model based on these human ratings has been developed (Benavente -et al-, 2008, JOSA-A, 25:10, 2582-2593). This computational model follows a fuzzy approach to assign a colour name to a particular RGB value. For example, a pixel with a value (255,0,0) will be named 'red' with membership 1, while a cyan pixel with a RGB value of (0, 200, 200) will be considered to be 0.5 green and 0.5 blue. In this work, we show how this colour naming paradigm can be applied to different computer vision tasks. In particular, we report results in colour constancy (Vazquez-Corral -et al-, 2012, IEEE TIP, in press) showing that the classical constraints on either illumination or surface reflectance can be substituted by the statistical properties encoded in the colour names. [Supported by projects TIN2010-21771-C02-1, CSD2007-00018]. |
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| Area | Expedition | Conference | AV A | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VBV2012 | Serial | 2131 | |||
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| Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco |
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| Title | An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction | Type |
Conference Article | |||
| Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | ||
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| Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. 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 (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) 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 visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM).
This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here. |
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| Area | Expedition | Conference | AV A | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ OPD2012a | Serial | 2132 | |||
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| Author | Jaime Moreno; Xavier Otazu |
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| Title | Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder | Type |
Conference Article | |||
| Year | 2011 | Publication | IEEE International Conference on Multimedia and Expo | Abbreviated Journal | ||
| Volume | Issue | Pages | 1-6 | |||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder. | |||||
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| ISSN | 1945-7871 | ISBN | 978-1-61284-348-3 | Medium | ||
| Area | Expedition | Conference | ICME | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ MoO2011a | Serial | 2176 | |||
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| Author | Jaime Moreno; Xavier Otazu |
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| Title | Image coder based on Hilbert scanning of embedded quadTrees | Type |
Conference Article | |||
| Year | 2011 | Publication | Data Compression Conference | Abbreviated Journal | ||
| Volume | Issue | Pages | 470-470 | |||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. | |||||
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| Area | Expedition | Conference | DCC | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ MoO2011b | Serial | 2177 | |||
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| Author | Jordi Roca; Maria Vanrell; C. Alejandro Parraga |
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| Title | What is constant in colour constancy? | Type |
Conference Article | |||
| Year | 2012 | Publication | 6th European Conference on Colour in Graphics, Imaging and Vision | Abbreviated Journal | ||
| Volume | Issue | Pages | 337-343 | |||
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| Abstract | Color constancy refers to the ability of the human visual system to stabilize
the color appearance of surfaces under an illuminant change. In this work we studied how the interrelations among nine colors are perceived under illuminant changes, particularly whether they remain stable across 10 different conditions (5 illuminants and 2 backgrounds). To do so we have used a paradigm that measures several colors under an immersive state of adaptation. From our measures we defined a perceptual structure descriptor that is up to 87% stable over all conditions, suggesting that color category features could be used to predict color constancy. This is in agreement with previous results on the stability of border categories [1,2] and with computational color constancy algorithms [3] for estimating the scene illuminant. |
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| ISSN | ISBN | 9781622767014 | Medium | |||
| Area | Expedition | Conference | CGIV | |||
| Notes | CIC | Approved | no | |||
| Call Number | RVP2012 | Serial | 2189 | |||
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| Author | Adria Ruiz; Joost Van de Weijer; Xavier Binefa |
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| Title | Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization | Type |
Conference Article | |||
| Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | ||
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| Abstract | We address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions and how they determine the video weak-labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized Multi-Concept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection. | |||||
| Address | Nottingham; UK; September 2014 | |||||
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| Area | Expedition | Conference | BMVC | |||
| Notes | LAMP; CIC; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ RWB2014 | Serial | 2508 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Michael Felsberg |
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| Title | Scale Coding Bag-of-Words for Action Recognition | Type |
Conference Article | |||
| Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 1514-1519 | |||
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| Abstract | Recognizing human actions in still images is a challenging problem in computer vision due to significant amount of scale, illumination and pose variation. Given the bounding box of a person both at training and test time, the task is to classify the action associated with each bounding box in an image.
Most state-of-the-art methods use the bag-of-words paradigm for action recognition. The bag-of-words framework employing a dense multi-scale grid sampling strategy is the de facto standard for feature detection. This results in a scale invariant image representation where all the features at multiple-scales are binned in a single histogram. We argue that such a scale invariant strategy is sub-optimal since it ignores the multi-scale information available with each bounding box of a person. This paper investigates alternative approaches to scale coding for action recognition in still images. We encode multi-scale information explicitly in three different histograms for small, medium and large scale visual-words. Our first approach exploits multi-scale information with respect to the image size. In our second approach, we encode multi-scale information relative to the size of the bounding box of a person instance. In each approach, the multi-scale histograms are then concatenated into a single representation for action classification. We validate our approaches on the Willow dataset which contains seven action categories: interacting with computer, photography, playing music, riding bike, riding horse, running and walking. Our results clearly suggest that the proposed scale coding approaches outperform the conventional scale invariant technique. Moreover, we show that our approach obtains promising results compared to more complex state-of-the-art methods. |
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| Address | Stockholm; August 2014 | |||||
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| Area | Expedition | Conference | ICPR | |||
| Notes | CIC; LAMP; 601.240; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ KWB2014 | Serial | 2450 | |||
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| Author | Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras |
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| Title | The Photometry of Intrinsic Images | Type |
Conference Article | |||
| Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 1494-1501 | |||
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| Abstract | Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images. | |||||
| Address | Columbus; Ohio; USA; June 2014 | |||||
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| Area | Expedition | Conference | CVPR | |||
| Notes | CIC; 600.052; 600.051; 600.074 | Approved | no | |||
| Call Number | Admin @ si @ SPB2014 | Serial | 2506 | |||
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| Author | M. Danelljan; Fahad Shahbaz Khan; Michael Felsberg; Joost Van de Weijer |
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| Title | Adaptive color attributes for real-time visual tracking | Type |
Conference Article | |||
| Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages | 1090 - 1097 | |||
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| Abstract | Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object
recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power. This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms state-of-the-art tracking methods while running at more than 100 frames per second. |
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| Address | Nottingham; UK; September 2014 | |||||
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| Area | Expedition | Conference | CVPR | |||
| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ DKF2014 | Serial | 2509 | |||
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| Author | Xavier Otazu; Olivier Penacchio; Xim Cerda-Company |
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| Title | Brightness and colour induction through contextual influences in V1 | Type |
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| Year | 2015 | Publication | Scottish Vision Group 2015 SGV2015 | Abbreviated Journal | ||
| Volume | 12 | Issue | 9 | Pages | 1208-2012 | |
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| Address | Carnoustie; Scotland; March 2015 | |||||
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| Area | Expedition | Conference | SGV | |||
| Notes | NEUROBIT;CIC | Approved | no | |||
| Call Number | Admin @ si @ OPC2015a | Serial | 2632 | |||
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| Author | Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris |
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| Title | Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code | Type |
Conference Article | |||
| Year | 2015 | Publication | European Conference on Visual Perception ECVP2015 | Abbreviated Journal | ||
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| Address | Liverpool; uk; August 2015 | |||||
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| Area | Expedition | Conference | ECVP | |||
| Notes | NEUROBIT;CIC | Approved | no | |||
| Call Number | Admin @ si @ POW2015 | Serial | 2633 | |||
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