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Author |
Xavier Baro; David Masip; Elena Planas; Julia Minguillon |
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Title  |
PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación |
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Miscellaneous |
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2013 |
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XV Jornadas de Enseñanza Universitaria de la Informatica |
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JENUI |
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OR;HuPBA;MV |
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no |
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Admin @ si @ BMP2013 |
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2237 |
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Author |
Jose Antonio Rodriguez |
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Title |
Pen-based Interfaces and Recognition: Application to Proofreading Interpretation |
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2006 |
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CVC Technical Report #96 |
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CVC (UAB) |
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Admin @ si @ Rod2006 |
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669 |
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Author |
Saiping Zhang, Luis Herranz, Marta Mrak, Marc Gorriz Blanch, Shuai Wan, Fuzheng Yang |
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Title |
PeQuENet: Perceptual Quality Enhancement of Compressed Video with Adaptation-and Attention-based Network |
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Miscellaneous |
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2022 |
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Arxiv |
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In this paper we propose a generative adversarial network (GAN) framework to enhance the perceptual quality of compressed videos. Our framework includes attention and adaptation to different quantization parameters (QPs) in a single model. The attention module exploits global receptive fields that can capture and align long-range correlations between consecutive frames, which can be beneficial for enhancing perceptual quality of videos. The frame to be enhanced is fed into the deep network together with its neighboring frames, and in the first stage features at different depths are extracted. Then extracted features are fed into attention blocks to explore global temporal correlations, followed by a series of upsampling and convolution layers. Finally, the resulting features are processed by the QP-conditional adaptation module which leverages the corresponding QP information. In this way, a single model can be used to enhance adaptively to various QPs without requiring multiple models specific for every QP value, while having similar performance. Experimental results demonstrate the superior performance of the proposed PeQuENet compared with the state-of-the-art compressed video quality enhancement algorithms. |
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MACO; no proj |
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Admin @ si @ ZHM2022b |
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3819 |
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Author |
Ivo Everts; Jan van Gemert; Theo Gevers |
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Title |
Per-patch Descriptor Selection using Surface and Scene Properties |
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2012 |
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12th European Conference on Computer Vision |
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7577 |
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VI |
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172-186 |
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Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool. |
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Florence, Italy |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-33782-6 |
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ECCV |
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ALTRES;ISE |
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no |
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Admin @ si @ EGG2012 |
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2023 |
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Author |
Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich |
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Title |
Perception Based Representations for Computational Colour |
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Conference Article |
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2011 |
Publication |
3rd International Workshop on Computational Color Imaging |
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6626 |
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16-30 |
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Keywords |
colour perception, induction, naming, psychophysical data, saliency, segmentation |
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Abstract |
The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. |
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Milan, Italy |
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Springer-Verlag |
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Raimondo Schettini, Shoji Tominaga, Alain Trémeau |
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978-3-642-20403-6 |
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CCIW |
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CIC |
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no |
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Call Number |
Admin @ si @ VMB2011 |
Serial |
1733 |
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Author |
Ramon Baldrich |
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Title |
Perceptual approach to a computational colour-texture representation for surface inspection. |
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Book Whole |
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2001 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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CIC |
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no |
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Call Number |
CAT @ cat @ Bal2001 |
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73 |
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Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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Title |
Perceptual color texture codebooks for retrieving in highly diverse texture datasets |
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Conference Article |
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2010 |
Publication |
20th International Conference on Pattern Recognition |
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866–869 |
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Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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CIC |
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no |
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CAT @ cat @ ASV2010b |
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1426 |
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Author |
Ramon Baldrich; Ricardo Toledo; Ernest Valveny; Maria Vanrell |
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Title |
Perceptual Colour Image Segmentation. |
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Miscellaneous |
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2002 |
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Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002: 145–150. |
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DAG;CIC;ADAS |
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no |
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CAT @ cat @ BTV2002 |
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290 |
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Author |
Jaime Moreno |
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Title |
Perceptual Criteria on Image Compresions |
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2011 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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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Ph.D. thesis |
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Ediciones Graficas Rey |
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Xavier Otazu |
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978-84-938351-3-2 |
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CIC |
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no |
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Admin @ si @ Mor2011 |
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1786 |
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Author |
Naila Murray |
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Perceptual Feature Detection |
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2009 |
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CVC Technical Report |
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131 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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Admin @ si @ Mur2009 |
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2390 |
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J.R. Serra; J.B. Subirana |
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Perceptual Grouping on Texture Images Using Non-Cartesian Networks |
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1996 |
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IEEE International Conference on Pattern Recognition. Vol B, pp. 462–466 |
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Admin @ si @ SeS1996a |
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217 |
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J.R. Serra; J.B. Subirana |
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Perceptual grouping on texture images using non-cartesian networks |
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1996 |
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CVC Technical Report #11 |
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CVC (UAB) |
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Admin @ si @ SeS1996b |
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218 |
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Author |
Marcos V Conde; Florin Vasluianu; Javier Vazquez; Radu Timofte |
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Perceptual image enhancement for smartphone real-time applications |
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2023 |
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Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision |
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1848-1858 |
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Recent advances in camera designs and imaging pipelines allow us to capture high-quality images using smartphones. However, due to the small size and lens limitations of the smartphone cameras, we commonly find artifacts or degradation in the processed images. The most common unpleasant effects are noise artifacts, diffraction artifacts, blur, and HDR overexposure. Deep learning methods for image restoration can successfully remove these artifacts. However, most approaches are not suitable for real-time applications on mobile devices due to their heavy computation and memory requirements. In this paper, we propose LPIENet, a lightweight network for perceptual image enhancement, with the focus on deploying it on smartphones. Our experiments show that, with much fewer parameters and operations, our model can deal with the mentioned artifacts and achieve competitive performance compared with state-of-the-art methods on standard benchmarks. Moreover, to prove the efficiency and reliability of our approach, we deployed the model directly on commercial smartphones and evaluated its performance. Our model can process 2K resolution images under 1 second in mid-level commercial smartphones. |
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Waikoloa; Hawai; USA; January 2023 |
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WACV |
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Notes |
MACO; CIC |
Approved |
no |
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Call Number |
Admin @ si @ CVV2023 |
Serial |
3900 |
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| Permanent link to this record |
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Author |
Marçal Rusiñol; Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny; Josep Llados |
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Title |
Perceptual Image Retrieval by Adding Color Information to the Shape Context Descriptor |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1594–1597 |
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Keywords |
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Abstract |
In this paper we present a method for the retrieval of images in terms of perceptual similarity. Local color information is added to the shape context descriptor in order to obtain an object description integrating both shape and color as visual cues. We use a color naming algorithm in order to represent the color information from a perceptual point of view. The proposed method has been tested in two different applications, an object retrieval scenario based on color sketch queries and a color trademark retrieval problem. Experimental results show that the addition of the color information significantly outperforms the sole use of the shape context descriptor. |
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Address |
Istanbul (Turkey) |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
Medium |
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Area |
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Expedition |
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Conference |
ICPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RNK2010 |
Serial |
1435 |
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| Permanent link to this record |
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Author |
Lluis Gomez |
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Title |
Perceptual Organization for Text Extraction in Natural Scenes |
Type |
Report |
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Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
173 |
Issue |
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Pages |
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Keywords |
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Abstract |
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Address |
Bellaterra |
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Corporate Author |
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Thesis |
Master's thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ Gom2012 |
Serial |
2309 |
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| Permanent link to this record |
