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Author |
Fadi Dornaika; Bogdan Raducanu |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation |
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Book Chapter |
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2012 |
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Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions |
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157-178 |
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NOVA Publishers |
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S.E. Carter |
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OR;MV |
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Admin @ si @ DoR2012 |
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2183 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Photometric Invariance by Machine Learning |
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Book Chapter |
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Year |
2012 |
Publication |
Color in Computer Vision: Fundamentals and Applications |
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Volume |
7 |
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113-134 |
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road detection |
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iConcept Press Ltd |
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Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek |
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978-0-470-89084-4 |
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ADAS |
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Admin @ si @ AlL2012 |
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2186 |
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Author |
Jose Manuel Alvarez; Y. LeCun; Theo Gevers; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Semantic Road Segmentation via Multi-Scale Ensembles of Learned Features |
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Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision – Workshops and Demonstrations |
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7584 |
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586-595 |
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road detection |
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Semantic segmentation refers to the process of assigning an object label (e.g., building, road, sidewalk, car, pedestrian) to every pixel in an image. Common approaches formulate the task as a random field labeling problem modeling the interactions between labels by combining local and contextual features such as color, depth, edges, SIFT or HoG. These models are trained to maximize the likelihood of the correct classification given a training set. However, these approaches rely on hand–designed features (e.g., texture, SIFT or HoG) and a higher computational time required in the inference process.
Therefore, in this paper, we focus on estimating the unary potentials of a conditional random field via ensembles of learned features. We propose an algorithm based on convolutional neural networks to learn local features from training data at different scales and resolutions. Then, diversification between these features is exploited using a weighted linear combination. Experiments on a publicly available database show the effectiveness of the proposed method to perform semantic road scene segmentation in still images. The algorithm outperforms appearance based methods and its performance is similar compared to state–of–the–art methods using other sources of information such as depth, motion or stereo. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-33867-0 |
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ECCVW |
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ADAS;ISE |
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Admin @ si @ ALG2012; ADAS @ adas |
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2187 |
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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 |
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Abstract |
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Year |
2012 |
Publication |
Perception |
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PER |
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41 |
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138 |
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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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0301-0066 |
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CIC |
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Admin @ si @ RPV2012 |
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2188 |
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Author |
Jordi Roca; Maria Vanrell; C. Alejandro Parraga |
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Title |
What is constant in colour constancy? |
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Conference Article |
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Year |
2012 |
Publication |
6th European Conference on Colour in Graphics, Imaging and Vision |
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337-343 |
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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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9781622767014 |
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CGIV |
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CIC |
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RVP2012 |
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2189 |
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Author |
Susana Alvarez |
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Title |
Revisión de la teoría de los Textons Enfoque computacional en color |
Type |
Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
El color y la textura son dos estímulos visuales importantes para la interpretación de las imágenes. La definición de descriptores computacionales que combinan estas dos características es aún un problema abierto. La dificultad se deriva esencialmente de la propia naturaleza de ambas, mientras que la textura es una propiedad de una región, el color es una propiedad de un punto.
Hasta ahora se han utilizado tres los tipos de aproximaciones para la combinación, (a) se describe la textura directamente en cada uno de los canales color, (b) se describen textura y color por separado y se combinan al final, y (c) la combinación se realiza con técnicas de aprendizaje automático. Considerando que este problema se resuelve en el sistema visual humano en niveles muy tempranos, en esta tesis se propone estudiar el problema a partir de la implementación directa de una teoría perceptual, la teoría de los textons, y explorar así su extensión a color.
Puesto que la teoría de los textons se basa en la descripción de la textura a partir de las densidades de los atributos locales, esto se adapta perfectamente al marco de trabajo de los descriptores holísticos (bag-of-words). Se han estudiado diversos descriptores basados en diferentes espacios de textons, y diferentes representaciones de las imágenes. Asimismo se ha estudiado la viabilidad de estos descriptores en una representación conceptual de nivel intermedio.
Los descriptores propuestos han demostrado ser muy eficientes en aplicaciones de recuperación y clasificación de imágenes, presentando ventajas en la generación de vocabularios. Los vocabularios se obtienen cuantificando directamente espacios de baja dimensión y la perceptualidad de estos espacios permite asociar semántica de bajo nivel a las palabras visuales. El estudio de los resultados permite concluir que si bien la aproximación holística es muy eficiente, la introducción de co-ocurrencia espacial de las propiedades de forma y color de los blobs de la imagen es un elemento clave para su combinación, hecho que no contradice las evidencias en percepción |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Maria Vanrell;Xavier Otazu |
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CIC |
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Alv2012b |
Serial |
2216 |
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Permanent link to this record |
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Author |
Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool |
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Title |
Active MAP Inference in CRFs for Efficient Semantic Segmentation |
Type |
Conference Article |
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Year |
2013 |
Publication |
15th IEEE International Conference on Computer Vision |
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2312 - 2319 |
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Semantic Segmentation |
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Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains. |
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Sydney; Australia; December 2013 |
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1550-5499 |
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ICCV |
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ADAS; 600.057 |
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ADAS @ adas @ RBN2013 |
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2377 |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo |
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Title |
Interactive Training of Human Detectors |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multiodal Interaction in Image and Video Applications |
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48 |
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169-182 |
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Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation |
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Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations. |
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Springer Heidelberg New York Dordrecht London |
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Springer Berlin Heidelberg |
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English |
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1868-4394 |
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978-3-642-35931-6 |
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ADAS; 600.057; 600.054; 605.203 |
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VLP2013; ADAS @ adas @ vlp2013 |
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2193 |
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Author |
Joan M. Nuñez; Debora Gil; Fernando Vilariño |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Finger joint characterization from X-ray images for rheymatoid arthritis assessment |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th International Conference on Biomedical Electronics and Devices |
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288-292 |
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Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde |
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In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection. |
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Barcelona; February 2013 |
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SciTePress |
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BIODEVICES |
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IAM;MV; 600.057; 600.054;SIAI |
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IAM @ iam @ NGV2013 |
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2196 |
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Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization |
Type |
Conference Article |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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1 |
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162-171 |
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Colonoscopy; Blood vessel; Linear features; Valley detection |
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This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance. |
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Barcelona; February 2013 |
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SciTePress |
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VISIGRAPP |
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MV; 600.054; 600.057;SIAI |
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IAM @ iam @ NBS2013 |
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2198 |
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Author |
Angel Sappa; Jordi Vitria |
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Title |
Multimodal Interaction in Image and Video Applications |
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Book Whole |
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2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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Abstract |
Book Series Intelligent Systems Reference Library |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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ADAS; OR;MV |
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no |
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Admin @ si @ SaV2013 |
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2199 |
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Author |
David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha |
![download PDF file pdf](img/file_PDF.gif)
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Title |
On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts |
Type |
Conference Article |
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Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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763-768 |
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document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding |
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he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20% |
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978-1-4673-2262-1 |
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ICFHR |
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Admin @ si @ FLF2012 |
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Ariel Amato |
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Environment-Independent Moving Cast Shadow Suppression in Video Surveillance |
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2012 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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This thesis is devoted to moving shadows detection and suppression. Shadows could be defined as the parts of the scene that are not directly illuminated by a light source due to obstructing object or objects. Often, moving shadows in images sequences are undesirable since they could cause degradation of the expected results during processing of images for object detection, segmentation, scene surveillance or similar purposes. In this thesis first moving shadow detection methods are exhaustively overviewed. Beside the mentioned methods from literature and to compensate their limitations a new moving shadow detection method is proposed. It requires no prior knowledge about the scene, nor is it restricted to assumptions about specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene the values of the background image are divided by values of the current frame in the RGB color space. In the thesis how this luminance ratio can be used to identify segments with low gradient constancy is shown, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of the proposed method compared with the most sophisticated state-of-the-art shadow detection algorithms. These results show that the proposed approach is robust and accurate over a broad range of shadow types and challenging video conditions. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Mikhail Mozerov;Jordi Gonzalez |
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Noha Elfiky |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Compact, Adaptive and Discriminative Spatial Pyramids for Improved Object and Scene Classification |
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2012 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The release of challenging datasets with a vast number of images, requires the development of efficient image representations and algorithms which are able to manipulate these large-scale datasets efficiently. Nowadays the Bag-of-Words (BoW) is the most successful approach in the context of object and scene classification tasks. However, its main drawback is the absence of the important spatial information. Spatial pyramids (SP) have been successfully applied to incorporate spatial information into BoW-based image representation. Observing the remarkable performance of spatial pyramids, their growing number of applications to a broad range of vision problems, and finally its geometry inclusion, a question can be asked what are the limits of spatial pyramids. Within the SP framework, the optimal way for obtaining an image spatial representation, which is able to cope with it’s most foremost shortcomings, concretely, it’s high dimensionality and the rigidity of the resulting image representation, still remains an active research domain. In summary, the main concern of this thesis is to search for the limits of spatial pyramids and try to figure out solutions for them. |
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Ediciones Graficas Rey |
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Jordi Gonzalez;Xavier Roca |
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Admin @ si @ Elf2012 |
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2202 |
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Author |
Marco Pedersoli |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Hierarchical Multiresolution Models for fast Object Detection |
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2012 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The ability to automatically detect and recognize objects in unconstrained images is becoming more and more critical: from security systems and autonomous robots, to smart phones and augmented reality, intelligent devices need to understand the meaning of images as a composition of semantic objects. This Thesis tackles the problem of fast object detection based on template models. Detection consists of searching for an object in an image by evaluating the similarity between a template model and an image region at each possible location and scale. In this work, we show that using a template model representation based on a multiple resolution hierarchy is an optimal choice that can lead to excellent detection accuracy and fast computation. We implement two different approaches that make use of a hierarchy of multiresolution models: a multiresolution cascade and a coarse-to-fine search. Also, we extend the coarse-to-fine search by introducing a deformable part-based model that achieves state-of-the-art results together with a very reduced computational cost. Finally, we specialize our approach to the challenging task of pedestrian detection from moving vehicles and show that the overall quality of the system outperforms previous works in terms of speed and accuracy. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Jordi Gonzalez;Xavier Roca |
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Admin @ si @ Ped2012 |
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2203 |
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