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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 | David Geronimo; Joan Serrat; Antonio Lopez; Ramon Baldrich |
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| Title | Traffic sign recognition for computer vision project-based learning | Type | Journal Article | |||
| Year | 2013 | Publication | IEEE Transactions on Education | Abbreviated Journal | T-EDUC | |
| Volume | 56 | Issue | 3 | Pages | 364-371 | |
| Keywords | traffic signs | |||||
| Abstract | This paper presents a graduate course project on computer vision. The aim of the project is to detect and recognize traffic signs in video sequences recorded by an on-board vehicle camera. This is a demanding problem, given that traffic sign recognition is one of the most challenging problems for driving assistance systems. Equally, it is motivating for the students given that it is a real-life problem. Furthermore, it gives them the opportunity to appreciate the difficulty of real-world vision problems and to assess the extent to which this problem can be solved by modern computer vision and pattern classification techniques taught in the classroom. The learning objectives of the course are introduced, as are the constraints imposed on its design, such as the diversity of students' background and the amount of time they and their instructors dedicate to the course. The paper also describes the course contents, schedule, and how the project-based learning approach is applied. The outcomes of the course are discussed, including both the students' marks and their personal feedback. | |||||
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| ISSN | 0018-9359 | ISBN | Medium | |||
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| Notes | ADAS; CIC | Approved | no | |||
| Call Number | Admin @ si @ GSL2013; ADAS @ adas @ | Serial | 2160 | |||
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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 | 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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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ OPD2012b | Serial | 2178 | |||
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| Author | Xavier Otazu |
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| Title | Perceptual tone-mapping operator based on multiresolution contrast decomposition | Type | Abstract | |||
| Year | 2012 | Publication | Perception | Abbreviated Journal | PER | |
| Volume | 41 | Issue | Pages | 86 | ||
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| Abstract | Tone-mapping operators (TMO) are used to display high dynamic range(HDR) images in low dynamic range (LDR) displays. Many computational and biologically inspired approaches have been used in the literature, being many of them based on multiresolution decompositions. In this work, a simple two stage model for TMO is presented. The first stage is a novel multiresolution contrast decomposition, which is inspired in a pyramidal contrast decomposition (Peli, 1990 Journal of the Optical Society of America7(10), 2032-2040).
This novel multiresolution decomposition represents the Michelson contrast of the image at different spatial scales. This multiresolution contrast representation, applied on the intensity channel of an opponent colour decomposition, is processed by a non-linear saturating model of V1 neurons (Albrecht et al, 2002 Journal ofNeurophysiology 88(2) 888-913). This saturation model depends on the visual frequency, and it has been modified in order to include information from the extended Contrast Sensitivity Function (e-CSF) (Otazu et al, 2010 Journal ofVision10(12) 5). A set of HDR images in Radiance RGBE format (from CIS HDR Photographic Survey and Greg Ward database) have been used to test the model, obtaining a set of LDR images. The resulting LDR images do not show the usual halo or color modification artifacts. |
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| ISSN | 0301-0066 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Ota2012 | Serial | 2179 | |||
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| Author | Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu |
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| Title | Switching off brightness induction through induction-reversed images | Type | Abstract | |||
| Year | 2012 | Publication | Perception | Abbreviated Journal | PER | |
| Volume | 41 | Issue | Pages | 208 | ||
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| Abstract | Brightness induction is the modulation of the perceived intensity of an
area by the luminance of surrounding areas. Although V1 is traditionally regarded as an area mostly responsive to retinal information, neurophysiological evidence suggests that it may explicitly represent brightness information. In this work, we investigate possible neural mechanisms underlying brightness induction. To this end, we consider the model by Z Li (1999 Computation and Neural Systems10187-212) which is constrained by neurophysiological data and focuses on the part of V1 responsible for contextual influences. This model, which has proven to account for phenomena such as contour detection and preattentive segmentation, shares with brightness induction the relevant effect of contextual influences. Importantly, the input to our network model derives from a complete multiscale and multiorientation wavelet decomposition, which makes it possible to recover an image reflecting the perceived luminance and successfully accounts for well known psychophysical effects for both static and dynamic contexts. By further considering inverse problem techniques we define induction-reversed images: given a target image, we build an image whose perceived luminance matches the actual luminance of the original stimulus, thus effectively canceling out brightness induction effects. We suggest that induction-reversed images may help remove undesired perceptual effects and can find potential applications in fields such as radiological image interpretation |
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ PDO2012a | Serial | 2180 | |||
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| Author | Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu |
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| Title | A Neurodynamical Model Of Brightness Induction In V1 Following Static And Dynamic Contextual Influences | Type | Abstract | |||
| Year | 2012 | Publication | 8th Federation of European Neurosciences | Abbreviated Journal | ||
| Volume | 6 | Issue | Pages | 63-64 | ||
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| Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Although striate cortex is traditionally regarded as an area mostly responsive to ensory (i.e. retinal) information,
neurophysiological evidence suggests that perceived brightness information mightbe explicitly represented in V1. Such evidence has been observed both in anesthetised cats where neuronal response modulations have been found to follow luminance changes outside the receptive felds and in human fMRI measurements. In this work, possible neural mechanisms that ofer a plausible explanation for such phenomenon are investigated. To this end, we consider the model proposed by Z.Li (Li, Network:Comput. Neural Syst., 10 (1999)) which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual infuences, i.e. layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has reproduced other phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant efect of contextual infuences. We have extended the original model such that the input to the network is obtained from a complete multiscale and multiorientation wavelet decomposition, thereby allowing the recovery of an image refecting the perceived intensity. The proposed model successfully accounts for well known psychophysical efects for static contexts (among them: the White's and modifed White's efects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction efects) and also for brigthness induction in dynamic contexts defned by modulating the luminance of surrounding areas (e.g. the brightness of a static central area is perceived to vary in antiphase to the sinusoidal luminance changes of its surroundings). This work thus suggests that intra-cortical interactions in V1 could partially explain perceptual brightness induction efects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual processing pathway. |
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| Area | Expedition | Conference | FENS | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ PDO2012b | Serial | 2181 | |||
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| Author | Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
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| Title | Predicting categorical colour perception in successive colour constancy | Type | Abstract | |||
| Year | 2012 | Publication | Perception | Abbreviated Journal | PER | |
| Volume | 41 | Issue | Pages | 138 | ||
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| Abstract | Colour constancy is a perceptual mechanism that seeks to keep the colour of objects relatively stable under an illumination shift. Experiments haveshown that its effects depend on the number of colours present in the scene. We
studied categorical colour changes under different adaptation states, in particular, whether the colour categories seen under a chromatically neutral illuminant are the same after a shift in the chromaticity of the illumination. To do this, we developed the chromatic setting paradigm (2011 Journal of Vision11 349), which is as an extension of achromatic setting to colour categories. The paradigm exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. Our experiments were run on a CRT monitor (inside a dark room) under various simulated illuminants and restricting the number of colours of the Mondrian background to three, thus weakening the adaptation effect. Our results show a change in the colour categories present before (under neutral illumination) and after adaptation (under coloured illuminants) with a tendency for adapted colours to be less saturated than before adaptation. This behaviour was predicted by a simple affine matrix model, adjusted to the chromatic setting results. |
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| ISSN | 0301-0066 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ RPV2012 | Serial | 2188 | |||
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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 | 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 | |||
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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 | Olivier Penacchio |
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| Title | Relative Density of L, M, S photoreceptors in the Human Retina | Type | Report | |||
| Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
| Volume | 135 | Issue | Pages | |||
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| Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
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Place of Publication | Bellaterra, Barcelona | Editor | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Pen2009 | Serial | 2394 | |||
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| Author | Xavier Boix |
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| Title | Learning Conditional Random Fields for Stereo | Type | Report | |||
| Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
| Volume | 136 | Issue | Pages | |||
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| Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
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Place of Publication | Bellaterra, Barcelona | Editor | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Boi2009 | Serial | 2395 | |||
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| Author | Shida Beigpour |
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| Title | Physics-based Reflectance Estimation Applied to Recoloring | Type | Report | |||
| Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
| Volume | 137 | Issue | Pages | |||
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| Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
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Place of Publication | Bellaterra, Barcelona | Editor | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Bei2009 | Serial | 2396 | |||
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| Author | Jose Carlos Rubio |
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| Title | Graph matching based on graphical models with application to vehicle tracking and classification at night | Type | Report | |||
| Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
| Volume | 144 | Issue | Pages | |||
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| Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
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Place of Publication | Bellaterra, Barcelona | Editor | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Rub2009 | Serial | 2398 | |||
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| Author | Ivet Rafegas |
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| Title | Exploring Low-Level Vision Models. Case Study: Saliency Prediction | Type | Report | |||
| Year | 2013 | Publication | CVC Technical Report | Abbreviated Journal | ||
| Volume | 175 | Issue | Pages | |||
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| Corporate Author | Thesis | Master's thesis | ||||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Raf2013 | Serial | 2409 | |||
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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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Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | BMVC | |||
| Notes | LAMP; CIC; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ RWB2014 | Serial | 2508 | |||
| Permanent link to this record | ||||||