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| Author | Cesar Isaza; Joaquin Salas; Bogdan Raducanu | ||||
| Title | Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors | Type | Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 10 | Pages | 13333-13348 |
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| Abstract | In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection. | ||||
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ ISR2012b | Serial | 2173 | ||
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| Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco | ||||
| 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 | Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu | ||||
| 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 | ||||
| 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 | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation | Type | Book Chapter | ||
| Year | 2012 | Publication | Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions | Abbreviated Journal | |
| Volume | Issue | Pages | 157-178 | ||
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| Publisher | NOVA Publishers | Place of Publication | Editor | S.E. Carter | |
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DoR2012 | Serial | 2183 | ||
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| Author | Jose Manuel Alvarez; Antonio Lopez | ||||
| Title | Photometric Invariance by Machine Learning | Type | Book Chapter | ||
| Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | |
| Volume | 7 | Issue | Pages | 113-134 | |
| Keywords | road detection | ||||
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| Publisher | iConcept Press Ltd | Place of Publication | Editor | Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek | |
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ISBN | 978-0-470-89084-4 | Medium | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ AlL2012 | Serial | 2186 | ||
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| Author | Jordi Roca; Maria Vanrell; C. Alejandro Parraga | ||||
| 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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ISBN | 9781622767014 | Medium | ||
| Area | Expedition | Conference | CGIV | ||
| Notes | CIC | Approved | no | ||
| Call Number | RVP2012 | Serial | 2189 | ||
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| Author | Susana Alvarez | ||||
| Title | Revisión de la teoría de los Textons Enfoque computacional en color | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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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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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell;Xavier Otazu | |
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| Notes | CIC | Approved | no | ||
| Call Number | Alv2012b | Serial | 2216 | ||
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| Author | David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha | ||||
| Title | On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts | Type | Conference Article | ||
| Year | 2012 | Publication | 13th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 763-768 | ||
| Keywords | 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 | ||||
| Abstract | 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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ISBN | 978-1-4673-2262-1 | Medium | ||
| Area | Expedition | Conference | ICFHR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FLF2012 | Serial | 2200 | ||
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| Author | Ariel Amato | ||||
| Title | Environment-Independent Moving Cast Shadow Suppression in Video Surveillance | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | 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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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Mikhail Mozerov;Jordi Gonzalez | |
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| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ Ama2012 | Serial | 2201 | ||
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| Author | Noha Elfiky | ||||
| Title | Compact, Adaptive and Discriminative Spatial Pyramids for Improved Object and Scene Classification | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | 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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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
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| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ Elf2012 | Serial | 2202 | ||
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| Author | Marco Pedersoli | ||||
| Title | Hierarchical Multiresolution Models for fast Object Detection | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | 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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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
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| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ Ped2012 | Serial | 2203 | ||
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| Author | Jaume Gibert | ||||
| Title | Vector Space Embedding of Graphs via Statistics of Labelling Information | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Pattern recognition is the task that aims at distinguishing objects among different classes. When such a task wants to be solved in an automatic way a crucial step is how to formally represent such patterns to the computer. Based on the different representational formalisms, we may distinguish between statistical and structural pattern recognition. The former describes objects as a set of measurements arranged in the form of what is called a feature vector. The latter assumes that relations between parts of the underlying objects need to be explicitly represented and thus it uses relational structures such as graphs for encoding their inherent information. Vector spaces are a very flexible mathematical structure that has allowed to come up with several efficient ways for the analysis of patterns under the form of feature vectors. Nevertheless, such a representation cannot explicitly cope with binary relations between parts of the objects and it is restricted to measure the exact same number of features for each pattern under study regardless of their complexity. Graph-based representations present the contrary situation. They can easily adapt to the inherent complexity of the patterns but introduce a problem of high computational complexity, hindering the design of efficient tools to process and analyse patterns.
Solving this paradox is the main goal of this thesis. The ideal situation for solving pattern recognition problems would be to represent the patterns using relational structures such as graphs, and to be able to use the wealthy repository of data processing tools from the statistical pattern recognition domain. An elegant solution to this problem is to transform the graph domain into a vector domain where any processing algorithm can be applied. In other words, by mapping each graph to a point in a vector space we automatically get access to the rich set of algorithms from the statistical domain to be applied in the graph domain. Such methodology is called graph embedding. In this thesis we propose to associate feature vectors to graphs in a simple and very efficient way by just putting attention on the labelling information that graphs store. In particular, we count frequencies of node labels and of edges between labels. Although their locality, these features are able to robustly represent structurally global properties of graphs, when considered together in the form of a vector. We initially deal with the case of discrete attributed graphs, where features are easy to compute. The continuous case is tackled as a natural generalization of the discrete one, where rather than counting node and edge labelling instances, we count statistics of some representatives of them. We encounter how the proposed vectorial representations of graphs suffer from high dimensionality and correlation among components and we face these problems by feature selection algorithms. We also explore how the diversity of different embedding representations can be exploited in order to boost the performance of base classifiers in a multiple classifier systems framework. An extensive experimental evaluation finally shows how the methodology we propose can be efficiently computed and compete with other graph matching and embedding methodologies. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Ernest Valveny | |
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ Gib2012 | Serial | 2204 | ||
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| Author | Mohammad Rouhani | ||||
| Title | Shape Representation and Registration using Implicit Functions | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Shape representation and registration are two important problems in computer vision and graphics. Representing the given cloud of points through an implicit function provides a higher level information describing the data. This representation can be more compact more robust to noise and outliers, hence it can be exploited in different computer vision application. In the first part of this thesis implicit shape representations, including both implicit B-spline and polynomial, are tackled. First, an approximation of a geometric distance is proposed to measure the closeness of the given cloud of points and the implicit surface. The analysis of the proposed distance shows an accurate estimation with smooth behavior. The distance by itself is used in a RANSAC based quadratic fitting method. Moreover, since the gradient information of the distance with respect to the surface parameters can be analytically computed, it is used in Levenberg-Marquadt algorithm to refine the surface parameters. In a different approach, an algebraic fitting method is used to represent an object through implicit B-splines. The outcome is a smooth flexible surface and can be represented in different levels from coarse to fine. This property has been exploited to solve the registration problem in the second part of the thesis. In the proposed registration technique the model set is replaced with an implicit representation provided in the first part; then, the point-to-point registration is converted to a point-to-model one in a higher level. This registration error can benefit from different distance estimations to speed up the registration process even without need of correspondence search. Finally, the non-rigid registration problem is tackled through a quadratic distance approximation that is based on the curvature information of the model set. This approximation is used in a free form deformation model to update its control lattice. Then it is shown how an accurate distance approximation can benefit non-rigid registration problems. | ||||
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Angel Sappa | |
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Rou2012 | Serial | 2205 | ||
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| Author | Jose Carlos Rubio | ||||
| Title | Many-to-Many High Order Matching. Applications to Tracking and Object Segmentation | Type | Book Whole | ||
| Year | 2012 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Feature matching is a fundamental problem in Computer Vision, having multiple applications such as tracking, image classification and retrieval, shape recognition and stereo fusion. In numerous domains, it is useful to represent the local structure of the matching features to increase the matching accuracy or to make the correspondence invariant to certain transformations (affine, homography, etc. . . ). However, encoding this knowledge requires complicating the model by establishing high-order relationships between the model elements, and therefore increasing the complexity of the optimization problem.
The importance of many-to-many matching is sometimes dismissed in the literature. Most methods are restricted to perform one-to-one matching, and are usually validated on synthetic, or non-realistic datasets. In a real challenging environment, with scale, pose and illumination variations of the object of interest, as well as the presence of occlusions, clutter, and noisy observations, many-to-many matching is necessary to achieve satisfactory results. As a consequence, finding the most likely many-to-many correspondence often involves a challenging combinatorial optimization process. In this work, we design and demonstrate matching algorithms that compute many-to-many correspondences, applied to several challenging problems. Our goal is to make use of high-order representations to improve the expressive power of the matching, at the same time that we make feasible the process of inference or optimization of such models. We effectively use graphical models as our preferred representation because they provide an elegant probabilistic framework to tackle structured prediction problems. We introduce a matching-based tracking algorithm which performs matching between frames of a video sequence in order to solve the difficult problem of headlight tracking at night-time. We also generalise this algorithm to solve the problem of data association applied to various tracking scenarios. We demonstrate the effectiveness of such approach in real video sequences and we show that our tracking algorithm can be used to improve the accuracy of a headlight classification system. In the second part of this work, we move from single (point) matching to dense (region) matching and we introduce a new hierarchical image representation. We make use of such model to develop a high-order many-to-many matching between pairs of images. We show that the use of high-order models in comparison to simpler models improves not only the accuracy of the results, but also the convergence speed of the inference algorithm. Finally, we keep exploiting the idea of region matching to design a fully unsupervised image co-segmentation algorithm that is able to perform competitively with state-of-the-art supervised methods. Our method also overcomes the typical drawbacks of some of the past works, such as avoiding the necessity of variate appearances on the image backgrounds. The region matching in this case is applied to effectively exploit inter-image information. We also extend this work to perform co-segmentation of videos, being the first time that such problem is addressed, as a way to perform video object segmentation |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Joan Serrat | |
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Rub2012 | Serial | 2206 | ||
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