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Author | Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title | Shadow Resistant Road Segmentation from a Mobile Monocular System | Type | Conference Article | |||
Year | 2007 | Publication | 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:9–16 | Abbreviated Journal | ||
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Keywords | road detection | |||||
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Address | Gerona (Spain) | |||||
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Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ ALB2007 | Serial | 943 | |||
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Author | Miquel Ferrer; Robert Benavente; Ernest Valveny; J. Garcia; Agata Lapedriza; Gemma Sanchez |
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Title | Aprendizaje Cooperativo Aplicado a la Docencia de las Asignaturas de Programacion en Ingenieria Informatica | Type | Miscellaneous | |||
Year | 2008 | Publication | Octava Jornada sobre Aprendizaje Cooperativo, 41–46 | Abbreviated Journal | ||
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Address | Lleida (Spain). | |||||
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Notes | OR;DAG;CIC;MV | Approved | no | |||
Call Number | BCNPCL @ bcnpcl @ FBV2008 | Serial | 955 | |||
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Author | Eduard Vazquez; Maria Vanrell |
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Title | Eines per al desenvolupament de competencies de enginyeria en un assignatura de Intel·ligencia Artificial | Type | Miscellaneous | |||
Year | 2008 | Publication | V Jornades d’Innovacio Docent (UAB) | Abbreviated Journal | ||
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Address | Bellaterra (Spain) | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ VaV2008 | Serial | 1011 | |||
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Author | Robert Benavente; Ernest Valveny; Jaume Garcia; Agata Lapedriza; Miquel Ferrer; Gemma Sanchez |
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Title | Una experiencia de adaptacion al EEES de las asignaturas de programacion en Ingenieria Informatica | Type | Miscellaneous | |||
Year | 2008 | Publication | V Congreso Iberoamericano de Docencia Universitaria, pp. 213–216 | Abbreviated Journal | ||
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Address | Valencia | |||||
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Notes | OR;DAG;CIC;MV | Approved | no | |||
Call Number | BCNPCL @ bcnpcl @ BVG2008 | Serial | 1031 | |||
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Author | Xavier Otazu; Maria Vanrell; C. Alejandro Parraga |
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Title | Colour induction effects are modelled by a low-level multiresolution wavelet framework | Type | Journal | |||
Year | 2008 | Publication | Perception 37(Suppl.): 107 | Abbreviated Journal | ||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ OVP2008b | Serial | 1055 | |||
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Author | Robert Benavente |
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Title | A Parametric Model for Computational Colour Naming | Type | Book Whole | |||
Year | 2007 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | PhD Thesis | |||||
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell | ||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ Ben2007 | Serial | 1108 | |||
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Author | Robert Benavente; Laura Igual; Fernando Vilariño |
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Title | Current Challenges in Computer Vision | Type | Book Whole | |||
Year | 2008 | Publication | Proccedings of the Third Internal Workshop | Abbreviated Journal | ||
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ISSN | ISBN | 978-84-936529-0-6 | Medium | |||
Area | Expedition | Conference | CVCRD | |||
Notes | MILAB;CIC;SIAI | Approved | no | |||
Call Number | BCNPCL @ bcnpcl @ BIV2008 | Serial | 1110 | |||
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Author | Marc Serra |
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Title | Estimating Intrinsic Images from Physical and Categorical Color Cues | Type | Report | |||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | ||
Volume | 151 | Issue | Pages | |||
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Corporate Author | Thesis | Master's thesis | ||||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Ser2010 | Serial | 1345 | |||
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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 | Joost Van de Weijer; Shida Beigpour |
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Title | The Dichromatic Reflection Model: Future Research Directions and Applications | Type | Conference Article | |||
Year | 2011 | Publication | International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | dblp | |||||
Abstract | The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability. | |||||
Address | Algarve, Portugal | |||||
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Publisher | SciTePress | Place of Publication | Editor | Mestetskiy, Leonid and Braz, José | ||
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ISSN | ISBN | 978-989-8425-47-8 | Medium | |||
Area | Expedition | Conference | VISIGRAPP | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ WeB2011 | Serial | 1778 | |||
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Author | Javier Vazquez |
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Title | Colour Constancy in Natural Through Colour Naming and Sensor Sharpening | Type | Book Whole | |||
Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.
To deal with the illuminant selection step, we hypothesise that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to the way that the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation. The implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant change. Consequently, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimised to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimise different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D. Several research lines still remain open. One natural extension would be to measure the effects of using the computed sharp sensors on the category hypothesis, while another might be to insert spatial contextual information to improve category hypothesis. Finally, much work still needs to be done to explore how individual sensors can be adjusted to the colours in a scene. |
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell;Graham D. Finlayson | ||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Vaz2011a | Serial | 1785 | |||
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Author | Jaime Moreno |
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Title | Perceptual Criteria on Image Compresions | Type | Book Whole | |||
Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Nowadays, digital images are used in many areas in everyday life, but they tend to be big. This increases amount of information leads us to the problem of image data storage. For example, it is common to have a representation a color pixel as a 24-bit number, where the channels red, green, and blue employ 8 bits each. In consequence, this kind of color pixel can specify one of 224 ¼ 16:78 million colors. Therefore, an image at a resolution of 512 £ 512 that allocates 24 bits per pixel, occupies 786,432 bytes. That is why image compression is important. An important feature of image compression is that it can be lossy or lossless. A compressed image is acceptable provided these losses of image information are not perceived by the eye. It is possible to assume that a portion of this information is redundant. Lossless Image Compression is defined as to mathematically decode the same image which was encoded. In Lossy Image Compression needs to identify two features inside the image: the redundancy and the irrelevancy of information. Thus, lossy compression modifies the image data in such a way when they are encoded and decoded, the recovered image is similar enough to the original one. How similar is the recovered image in comparison to the original image is defined prior to the compression process, and it depends on the implementation to be performed. In lossy compression, current image compression schemes remove information considered irrelevant by using mathematical criteria. One of the problems of these schemes is that although the numerical quality of the compressed image is low, it shows a high visual image quality, e.g. it does not show a lot of visible artifacts. It is because these mathematical criteria, used to remove information, do not take into account if the viewed information is perceived by the Human Visual System. Therefore, the aim of an image compression scheme designed to obtain images that do not show artifacts although their numerical quality can be low, is to eliminate the information that is not visible by the Human Visual System. Hence, this Ph.D. thesis proposes to exploit the visual redundancy existing in an image by reducing those features that can be unperceivable for the Human Visual System. First, we define an image quality assessment, which is highly correlated with the psychophysical experiments performed by human observers. The proposed CwPSNR metrics weights the well-known PSNR by using a particular perceptual low level model of the Human Visual System, e.g. the Chromatic Induction Wavelet Model (CIWaM). Second, we propose an image compression algorithm (called Hi-SET), which exploits the high correlation and self-similarity of pixels in a given area or neighborhood by means of a fractal function. Hi-SET possesses the main features that modern image compressors have, that is, it is an embedded coder, which allows a progressive transmission. Third, we propose a perceptual quantizer (½SQ), which is a modification of the uniform scalar quantizer. The ½SQ is applied to a pixel set in a certain Wavelet sub-band, that is, a global quantization. Unlike this, the proposed modification allows to perform a local pixel-by-pixel forward and inverse quantization, introducing into this process a perceptual distortion which depends on the surround spatial information of the pixel. Combining ½SQ method with the Hi-SET image compressor, we define a perceptual image compressor, called ©SET. Finally, a coding method for Region of Interest areas is presented, ½GBbBShift, which perceptually weights pixels into these areas and maintains only the more important perceivable features in the rest of the image. Results presented in this report show that CwPSNR is the best-ranked image quality method when it is applied to the most common image compression distortions such as JPEG and JPEG2000. CwPSNR shows the best correlation with the judgement of human observers, which is based on the results of psychophysical experiments obtained for relevant image quality databases such as TID2008, LIVE, CSIQ and IVC. Furthermore, Hi-SET coder obtains better results both for compression ratios and perceptual image quality than the JPEG2000 coder and other coders that use a Hilbert Fractal for image compression. Hence, when the proposed perceptual quantization is introduced to Hi-SET coder, our compressor improves its numerical and perceptual e±ciency. When ½GBbBShift method applied to Hi-SET is compared against MaxShift method applied to the JPEG2000 standard and Hi-SET, the images coded by our ROI method get the best results when the overall image quality is estimated. Both the proposed perceptual quantization and the ½GBbBShift method are generalized algorithms that can be applied to other Wavelet based image compression algorithms such as JPEG2000, SPIHT or SPECK. | |||||
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Xavier Otazu | ||
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ISSN | ISBN | 978-84-938351-3-2 | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Mor2011 | Serial | 1786 | |||
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Author | Eduard Vazquez |
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Title | Unsupervised image segmentation based on material reflectance description and saliency | Type | Book Whole | |||
Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Image segmentations aims to partition an image into a set of non-overlapped regions, called segments. Despite the simplicity of the definition, image segmentation raises as a very complex problem in all its stages. The definition of segment is still unclear. When asking to a human to perform a segmentation, this person segments at different levels of abstraction. Some segments might be a single, well-defined texture whereas some others correspond with an object in the scene which might including multiple textures and colors. For this reason, segmentation is divided in bottom-up segmentation and top-down segmentation. Bottom up-segmentation is problem independent, that is, focused on general properties of the images such as textures or illumination. Top-down segmentation is a problem-dependent approach which looks for specific entities in the scene, such as known objects. This work is focused on bottom-up segmentation. Beginning from the analysis of the lacks of current methods, we propose an approach called RAD. Our approach overcomes the main shortcomings of those methods which use the physics of the light to perform the segmentation. RAD is a topological approach which describes a single-material reflectance. Afterwards, we cope with one of the main problems in image segmentation: non supervised adaptability to image content. To yield a non-supervised method, we use a model of saliency yet presented in this thesis. It computes the saliency of the chromatic transitions of an image by means of a statistical analysis of the images derivatives. This method of saliency is used to build our final approach of segmentation: spRAD. This method is a non-supervised segmentation approach. Our saliency approach has been validated with a psychophysical experiment as well as computationally, overcoming a state-of-the-art saliency method. spRAD also outperforms state-of-the-art segmentation techniques as results obtained with a widely-used segmentation dataset show | |||||
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Place of Publication | Editor | Ramon Baldrich | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Vaz2011b | Serial | 1835 | |||
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Author | Fahad Shahbaz Khan |
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Title | Coloring bag-of-words based image representations | Type | Book Whole | |||
Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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Abstract | Put succinctly, the bag-of-words based image representation is the most successful approach for object and scene recognition. Within the bag-of-words framework the optimal fusion of multiple cues, such as shape, texture and color, still remains an active research domain. There exist two main approaches to combine color and shape information within the bag-of-words framework. The first approach called, early fusion, fuses color and shape at the feature level as a result of which a joint colorshape vocabulary is produced. The second approach, called late fusion, concatenates histogram representation of both color and shape, obtained independently. In the first part of this thesis, we analyze the theoretical implications of both early and late feature fusion. We demonstrate that both these approaches are suboptimal for a subset of object categories. Consequently, we propose a novel method for recognizing object categories when using multiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom-up and top-down attention maps. Subsequently, the color attention maps are used to modulate the weights of the shape features. Shape features are given more weight in regions with higher attention and vice versa. The approach is tested on several benchmark object recognition data sets and the results clearly demonstrate the effectiveness of our proposed method. In the second part of the thesis, we investigate the problem of obtaining compact spatial pyramid representations for object and scene recognition. Spatial pyramids have been successfully applied to incorporate spatial information into bag-of-words based image representation. However, a major drawback of spatial pyramids is that it leads to high dimensional image representations. We present a novel framework for obtaining compact pyramid representation. The approach reduces the size of a high dimensional pyramid representation upto an order of magnitude without any significant reduction in accuracy. Moreover, we also investigate the optimal combination of multiple features such as color and shape within the context of our compact pyramid representation. Finally, we describe a novel technique to build discriminative visual words from multiple cues learned independently from training images. To this end, we use an information theoretic vocabulary compression technique to find discriminative combinations of visual cues and the resulting visual vocabulary is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. The approach is tested on standard object recognition data sets. The results obtained clearly demonstrate the effectiveness of our approach. | |||||
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Corporate Author | Thesis | Ph.D. thesis | ||||
Publisher | Place of Publication | Editor | Joost Van de Weijer;Maria Vanrell | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Kha2011 | Serial | 1838 | |||
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Author | Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell |
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Title | Portmanteau Vocabularies for Multi-Cue Image Representation | Type | Conference Article | |||
Year | 2011 | Publication | 25th Annual Conference on Neural Information Processing Systems | Abbreviated Journal | ||
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Abstract | We describe a novel technique for feature combination in the bag-of-words model of image classification. Our approach builds discriminative compound words from primitive cues learned independently from training images. Our main observation is that modeling joint-cue distributions independently is more statistically robust for typical classification problems than attempting to empirically estimate the dependent, joint-cue distribution directly. We use Information theoretic vocabulary compression to find discriminative combinations of cues and the resulting vocabulary of portmanteau words is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. State-of-the-art results on both the Oxford Flower-102 and Caltech-UCSD Bird-200 datasets demonstrate the effectiveness of our technique compared to other, significantly more complex approaches to multi-cue image representation | |||||
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Area | Expedition | Conference | NIPS | |||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ KWB2011 | Serial | 1865 | |||
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Author | Naila Murray |
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Title | Perceptual Feature Detection | Type | Report | |||
Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
Volume | 131 | Issue | Pages | |||
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Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
Publisher | Place of Publication | Bellaterra, Barcelona | Editor | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ Mur2009 | Serial | 2390 | |||
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Author | Maria del Camp Davesa |
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Title | Human action categorization in image sequences | Type | Report | |||
Year | 2011 | Publication | CVC Technical Report | Abbreviated Journal | ||
Volume | 169 | Issue | Pages | |||
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Address | Bellaterra (Spain) | |||||
Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
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Notes | CiC;CIC | Approved | no | |||
Call Number | Admin @ si @ Dav2011 | Serial | 1934 | |||
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Author | Albert Gordo |
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Title | A Cyclic Page Layout Descriptor for Document Classification & Retrieval | Type | Report | |||
Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | ||
Volume | 128 | Issue | Pages | |||
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Corporate Author | Computer Vision Center | Thesis | Master's thesis | |||
Publisher | Place of Publication | Bellaterra, Barcelona | Editor | |||
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Notes | CIC;DAG | Approved | no | |||
Call Number | Admin @ si @ Gor2009 | Serial | 2387 | |||
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