Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	2716–2730 of 3413 records found matching your query (RSS):

Search & Display Options

Select All Deselect All

[171–180] << 181 182 183 184 185 186 187 188 189 190 >> [191–200]

List View

Citations

Details

	Records
	Author	Javier Vazquez; G. D. Finlayson; Maria Vanrell
	Title	A compact singularity function to predict WCS data and unique hues			Type	Conference Article
	Year	2010	Publication	5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science	Abbreviated Journal
	Volume		Issue		Pages	33–38
	Keywords
	Abstract	Understanding how colour is used by the human vision system is a widely studied research field. The field, though quite advanced, still faces important unanswered questions. One of them is the explanation of the unique hues and the assignment of color names. This problem addresses the fact of different perceptual status for different colors. Recently, Philipona and O'Regan have proposed a biological model that allows to extract the reflection properties of any surface independently of the lighting conditions. These invariant properties are the basis to compute a singularity index that predicts the asymmetries presented in unique hues and basic color categories psychophysical data, therefore is giving a further step in their explanation. In this paper we build on their formulation and propose a new singularity index. This new formulation equally accounts for the location of the 4 peaks of the World colour survey and has two main advantages. First, it is a simple elegant numerical measure (the Philipona measurement is a rather cumbersome formula). Second, we develop a colour-based explanation for the measure.
	Address	Joensuu, Finland
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	9781617388897	Medium
	Area		Expedition		Conference	CGIV/MCS
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ VFV2010			Serial	1324
Permanent link to this record



	Author	C. Alejandro Parraga; Robert Benavente; Maria Vanrell
	Title	Towards a general model of colour categorization which considers context			Type	Journal Article
	Year	2010	Publication	Perception. ECVP Abstract Supplement	Abbreviated Journal	PER
	Volume	39	Issue		Pages	86
	Keywords
	Abstract	In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured. In the ﬁrst experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to ﬁnd the boundary between pairs of adjacent colours. Results from these experiments showed signiﬁcant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the ﬁrst experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that although boundary locations are very similar, boundaries measured in context are signiﬁcantly dierent(more diuse) than those measured in isolation (conﬁrmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ PBV2010b			Serial	1326
Permanent link to this record



	Author	Javier Vazquez; Maria Vanrell; Robert Benavente
	Title	Color names as a constraint for Computer Vision problems			Type	Conference Article
	Year	2010	Publication	Proceedings of The CREATE 2010 Conference	Abbreviated Journal
	Volume		Issue		Pages	324–328
	Keywords
	Abstract	Computer Vision Problems are usually ill-posed. Constraining de gamut of possible solutions is then a necessary step. Many constrains for different problems have been developed during years. In this paper, we present a different way of constraining some of these problems: the use of color names. In particular, we will focus on segmentation, representation ans constancy.
	Address	Gjovik (Norway)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CREATE
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ VVB2010			Serial	1328
Permanent link to this record



	Author	Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell
	Title	Who Painted this Painting?			Type	Conference Article
	Year	2010	Publication	Proceedings of The CREATE 2010 Conference	Abbreviated Journal
	Volume		Issue		Pages	329–333
	Keywords
	Abstract
	Address	Gjovik (Norway)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CREATE
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ KWV2010			Serial	1329
Permanent link to this record



	Author	Shida Beigpour; Joost Van de Weijer
	Title	Photo-Realistic Color Alteration for Architecture and Design			Type	Conference Article
	Year	2010	Publication	Proceedings of The CREATE 2010 Conference	Abbreviated Journal
	Volume		Issue		Pages	84–88
	Keywords
	Abstract	As color is a strong stimuli we receive from the exterior world, choosing the right color can prove crucial in creating the desired architecture and desing. We propose a framework to apply a realistic color change on both objects and their illuminant lights for snapshots of architectural designs, in order to visualize and choose the right color before actully applying the change in the real world. The proposed framework is based on the laws of physics in order to accomplish realistic and physically plausible results.
	Address	Gjovik (Norway)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CREATE
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ BeW2010			Serial	1330
Permanent link to this record



	Author	Ignasi Rius
	Title	Motion Priors for Efficient Bayesian Tracking in Human Sequence Evaluation			Type	Book Whole
	Year	2010	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Recovering human motion by visual analysis is a challenging computer vision research area with a lot of potential applications. Model-based tracking approaches, and in particular particle lters, formulate the problem as a Bayesian inference task whose aim is to sequentially estimate the distribution of the parameters of a human body model over time. These approaches strongly rely on good dynamical and observation models to predict and update congurations of the human body according to measurements from the image data. However, it is very dicult to design observation models which extract useful and reliable information from image sequences robustly. This results specially challenging in monocular tracking given that only one viewpoint from the scene is available. Therefore, to overcome these limitations strong motion priors are needed to guide the exploration of the state space. The work presented in this Thesis is aimed to retrieve the 3D motion parameters of a human body model from incomplete and noisy measurements of a monocular image sequence. These measurements consist of the 2D positions of a reduced set of joints in the image plane. Towards this end, we present a novel action-specic model of human motion which is trained from several databases of real motion-captured performances of an action, and is used as a priori knowledge within a particle ltering scheme. Body postures are represented by means of a simple and compact stick gure model which uses direction cosines to represent the direction of body limbs in the 3D Cartesian space. Then, for a given action, Principal Component Analysis is applied to the training data to perform dimensionality reduction over the highly correlated input data. Before the learning stage of the action model, the input motion performances are synchronized by means of a novel dense matching algorithm based on Dynamic Programming. The algorithm synchronizes all the motion sequences of the same action class, nding an optimal solution in real-time. Then, a probabilistic action model is learnt, based on the synchronized motion examples, which captures the variability and temporal evolution of full-body motion within a specic action. In particular, for each action, the parameters learnt are: a representative manifold for the action consisting of its mean performance, the standard deviation from the mean performance, the mean observed direction vectors from each motion subsequence of a given length and the expected error at a given time instant. Subsequently, the action-specic model is used as a priori knowledge on human motion which improves the eciency and robustness of the overall particle filtering tracking framework. First, the dynamic model guides the particles according to similar situations previously learnt. Then, the state space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, the state space is explored more eciently as the particle set covers the most probable body postures. Finally, experiments are carried out using test sequences from several motion databases. Results point out that our tracker scheme is able to estimate the rough 3D conguration of a full-body model providing only the 2D positions of a reduced set of joints. Separate tests on the sequence synchronization method and the subsequence probabilistic matching technique are also provided.
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Jordi Gonzalez;Xavier Roca
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-937261-9-5	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ Riu2010			Serial	1331
Permanent link to this record



	Author	Ivan Huerta
	Title	Foreground Object Segmentation and Shadow Detection for Video Sequences in Uncontrolled Environments			Type	Book Whole
	Year	2010	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	This Thesis is mainly divided in two parts. The first one presents a study of motion segmentation problems. Based on this study, a novel algorithm for mobile-object segmentation from a static background scene is also presented. This approach is demonstrated robust and accurate under most of the common problems in motion segmentation. The second one tackles the problem of shadows in depth. Firstly, a bottom-up approach based on a chromatic shadow detector is presented to deal with umbra shadows. Secondly, a top-down approach based on a tracking system has been developed in order to enhance the chromatic shadow detection. In our first contribution, a case analysis of motion segmentation problems is presented by taking into account the problems associated with different cues, namely colour, edge and intensity. Our second contribution is a hybrid architecture which handles the main problems observed in such a case analysis, by fusing (i) the knowledge from these three cues and (ii) a temporal difference algorithm. On the one hand, we enhance the colour and edge models to solve both global/local illumination changes (shadows and highlights) and camouflage in intensity. In addition, local information is exploited to cope with a very challenging problem such as the camouflage in chroma. On the other hand, the intensity cue is also applied when colour and edge cues are not available, such as when beyond the dynamic range. Additionally, temporal difference is included to segment motion when these three cues are not available, such as that background not visible during the training period. Lastly, the approach is enhanced for allowing ghost detection. As a result, our approach obtains very accurate and robust motion segmentation in both indoor and outdoor scenarios, as quantitatively and qualitatively demonstrated in the experimental results, by comparing our approach with most best-known state-of-the-art approaches. Motion Segmentation has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. Firstly, a bottom-up approach for detection and removal of chromatic moving shadows in surveillance scenarios is proposed. Secondly, a top-down approach based on kalman filters to detect and track shadows has been developed in order to enhance the chromatic shadow detection. In the Bottom-up part, the shadow detection approach applies a novel technique based on gradient and colour models for separating chromatic moving shadows from moving objects. Well-known colour and gradient models are extended and improved into an invariant colour cone model and an invariant gradient model, respectively, to perform automatic segmentation while detecting potential shadows. Hereafter, the regions corresponding to potential shadows are grouped by considering ”a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between local gradient structures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. In the top-down process, after detection of objects and shadows both are tracked using Kalman filters, in order to enhance the chromatic shadow detection, when it fails to detect a shadow. Firstly, this implies a data association between the blobs (foreground and shadow) and Kalman filters. Secondly, an event analysis of the different data association cases is performed, and occlusion handling is managed by a Probabilistic Appearance Model (PAM). Based on this association, temporal consistency is looked for the association between foregrounds and shadows and their respective Kalman Filters. From this association several cases are studied, as a result lost chromatic shadows are correctly detected. Finally, the tracking results are used as feedback to improve the shadow and object detection. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions.
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Jordi Gonzalez;Xavier Roca
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-937261-3-3	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	ISE @ ise @ Hue2010			Serial	1332
Permanent link to this record



	Author	Carles Fernandez
	Title	Understanding Image Sequences: the Role of Ontologies in Cognitive Vision			Type	Book Whole
	Year	2010	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. In this thesis we tackle the problem of recognizing and describing meaningful events in video sequences from different domains, and communicating the resulting knowledge to end-users by means of advanced interfaces for human–computer interaction. This problem is addressed by designing the high-level modules of a cognitive vision framework exploiting ontological knowledge. Ontologies allow us to define the relevant concepts in a domain and the relationships among them; we prove that the use of ontologies to organize, centralize, link, and reuse different types of knowledge is a key factor in the materialization of our objectives. The proposed framework contributes to: (i) automatically learn the characteristics of different scenarios in a domain; (ii) reason about uncertain, incomplete, or vague information from visual –camera’s– or linguistic –end-user’s– inputs; (iii) derive plausible interpretations of complex events from basic spatiotemporal developments; (iv) facilitate natural interfaces that adapt to the needs of end-users, and allow them to communicate efficiently with the system at different levels of interaction; and finally, (v) find mechanisms to guide modeling processes, maintain and extend the resulting models, and to exploit multimodal resources synergically to enhance the former tasks. We describe a holistic methodology to achieve these goals. First, the use of prior taxonomical knowledge is proved useful to guide MAP-MRF inference processes in the automatic identification of semantic regions, with independence of a particular scenario. Towards the recognition of complex video events, we combine fuzzy metric-temporal reasoning with SGTs, thus assessing high-level interpretations from spatiotemporal data. Here, ontological resources like T–Boxes, onomasticons, or factual databases become useful to derive video indexing and retrieval capabilities, and also to forward highlighted content to smart user interfaces. There, we explore the application of ontologies to discourse analysis and cognitive linguistic principles, or scene augmentation techniques towards advanced communication by means of natural language dialogs and synthetic visualizations. Ontologies become fundamental to coordinate, adapt, and reuse the different modules in the system. The suitability of our ontological framework is demonstrated by a series of applications that especially benefit the field of smart video surveillance, viz. automatic generation of linguistic reports about the content of video sequences in multiple natural languages; content-based filtering and summarization of these reports; dialogue-based interfaces to query and browse video contents; automatic learning of semantic regions in a scenario; and tools to evaluate the performance of components and models in the system, via simulation and augmented reality.
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Jordi Gonzalez;Xavier Roca
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-937261-2-6	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ Fer2010a			Serial	1333
Permanent link to this record



	Author	Joan Mas
	Title	A Syntactic Pattern Recognition Approach based on a Distribution Tolerant Adjacency Grammar and a Spatial Indexed Parser. Application to Sketched Document Recognition			Type	Book Whole
	Year	2010	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Sketch recognition is a discipline which has gained an increasing interest in the last 20 years. This is due to the appearance of new devices such as PDA, Tablet PC’s or digital pen & paper protocols. From the wide range of sketched documents we focus on those that represent structured documents such as: architectural floor-plans, engineering drawing, UML diagrams, etc. To recognize and understand these kinds of documents, first we have to recognize the different compounding symbols and then we have to identify the relations between these elements. From the way that a sketch is captured, there are two categories: on-line and off-line. On-line input modes refer to draw directly on a PDA or a Tablet PC’s while off-line input modes refer to scan a previously drawn sketch. This thesis is an overlapping of three different areas on Computer Science: Pattern Recognition, Document Analysis and Human-Computer Interaction. The aim of this thesis is to interpret sketched documents independently on whether they are captured on-line or off-line. For this reason, the proposed approach should contain the following features. First, as we are working with sketches the elements present in our input contain distortions. Second, as we would work in on-line or off-line input modes, the order in the input of the primitives is indifferent. Finally, the proposed method should be applied in real scenarios, its response time must be slow. To interpret a sketched document we propose a syntactic approach. A syntactic approach is composed of two correlated components: a grammar and a parser. The grammar allows describing the different elements on the document as well as their relations. The parser, given a document checks whether it belongs to the language generated by the grammar or not. Thus, the grammar should be able to cope with the distortions appearing on the instances of the elements. Moreover, it would be necessary to define a symbol independently of the order of their primitives. Concerning to the parser when analyzing 2D sentences, it does not assume an order in the primitives. Then, at each new primitive in the input, the parser searches among the previous analyzed symbols candidates to produce a valid reduction. Taking into account these features, we have proposed a grammar based on Adjacency Grammars. This kind of grammars defines their productions as a multiset of symbols rather than a list. This allows describing a symbol without an order in their components. To cope with distortion we have proposed a distortion model. This distortion model is an attributed estimated over the constraints of the grammar and passed through the productions. This measure gives an idea on how far is the symbol from its ideal model. In addition to the distortion on the constraints other distortions appear when working with sketches. These distortions are: overtracing, overlapping, gaps or spurious strokes. Some grammatical productions have been defined to cope with these errors. Concerning the recognition, we have proposed an incremental parser with an indexation mechanism. Incremental parsers analyze the input symbol by symbol given a response to the user when a primitive is analyzed. This makes incremental parser suitable to work in on-line as well as off-line input modes. The parser has been adapted with an indexation mechanism based on a spatial division. This indexation mechanism allows setting the primitives in the space and reducing the search to a neighbourhood. A third contribution is a grammatical inference algorithm. This method given a set of symbols captures the production describing it. In the field of formal languages, different approaches has been proposed but in the graphical domain not so much work is done in this field. The proposed method is able to capture the production from a set of symbol although they are drawn in different order. A matching step based on the Haussdorff distance and the Hungarian method has been proposed to match the primitives of the different symbols. In addition the proposed approach is able to capture the variability in the parameters of the constraints. From the experimental results, we may conclude that we have proposed a robust approach to describe and recognize sketches. Moreover, the addition of new symbols to the alphabet is not restricted to an expert. Finally, the proposed approach has been used in two real scenarios obtaining a good performance.
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Gemma Sanchez;Josep Llados
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-937261-4-0	Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ Mas2010			Serial	1334
Permanent link to this record



	Author	Francisco Javier Orozco
	Title	Human Emotion Evaluation on Facial Image Sequences			Type	Book Whole
	Year	2010	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Psychological evidence has emphasized the importance of affective behaviour understanding due to its high impact in nowadays interaction humans and computers. All type of affective and behavioural patterns such as gestures, emotions and mental states are highly displayed through the face, head and body. Therefore, this thesis is focused to analyse affective behaviours on head and face. To this end, head and facial movements are encoded by using appearance based tracking methods. Specifically, a wise combination of deformable models captures rigid and non-rigid movements of different kinematics; 3D head pose, eyebrows, mouth, eyelids and irises are taken into account as basis for extracting features from databases of video sequences. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques. For about thirty years, computer sciences have addressed the investigation on human emotions to the automatic recognition of six prototypic emotions suggested by Darwin and systematized by Paul Ekman in the seventies. The Facial Action Coding System (FACS) which uses discrete movements of the face (called Action units or AUs) to code the six facial emotions named anger, disgust, fear, happy-Joy, sadness and surprise. However, human emotions are much complex patterns that have not received the same attention from computer scientists. Simon Baron-Cohen proposed a new taxonomy of emotions and mental states without a system coding of the facial actions. These 426 affective behaviours are more challenging for the understanding of human emotions. Beyond of classically classifying the six basic facial expressions, more subtle gestures, facial actions and spontaneous emotions are considered here. By assessing confidence on the recognition results, exploring spatial and temporal relationships of the features, some methods are combined and enhanced for developing new taxonomy of expressions and emotions. The objective of this dissertation is to develop a computer vision system, including both facial feature extraction, expression recognition and emotion understanding by building a bottom-up reasoning process. Building a detailed taxonomy of human affective behaviours is an interesting challenge for head-face-based image analysis methods. In this paper, we exploit the strengths of Canonical Correlation Analysis (CCA) to enhance an on-line head-face tracker. A relationship between head pose and local facial movements is studied according to their cognitive interpretation on affective expressions and emotions. Active Shape Models are synthesized for AAMs based on CCA-regression. Head pose and facial actions are fused into a maximally correlated space in order to assess expressiveness, confidence and classification in a CBR system. The CBR solutions are also correlated to the cognitive features, which allow avoiding exhaustive search when recognizing new head-face features. Subsequently, Support Vector Machines (SVMs) and Bayesian Networks are applied for learning the spatial relationships of facial expressions. Similarly, the temporal evolution of facial expressions, emotion and mental states are analysed based on Factorized Dynamic Bayesian Networks (FaDBN). As results, the bottom-up system recognizes six facial expressions, six basic emotions and six mental states, plus enhancing this categorization with confidence assessment at each level, intensity of expressions and a complete taxonomy
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Jordi Gonzalez;Xavier Roca
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-936529-3-7	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ Oro2010			Serial	1335
Permanent link to this record



	Author	Marc Serra
	Title	Estimating Intrinsic Images from Physical and Categorical Color Cues			Type	Report
	Year	2010	Publication	CVC Technical Report	Abbreviated Journal
	Volume	151	Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis	Master's thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ Ser2010			Serial	1345
Permanent link to this record



	Author	Ahmed Mounir Gad
	Title	Object Localization Enhancement by Multiple Segmentation Fusion			Type	Report
	Year	2010	Publication	CVC Technical Report	Abbreviated Journal
	Volume	152	Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis	Master's thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ Mou2010			Serial	1346
Permanent link to this record



	Author	Antonio Hernandez
	Title	Pose and Face Recovery via Spatio-temporal GrabCut Human Segmentation			Type	Report
	Year	2010	Publication	CVC Technical Report	Abbreviated Journal
	Volume	153	Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis	Master's thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ Her2010			Serial	1347
Permanent link to this record



	Author	Jorge Bernal; Fernando Vilariño; F. Javier Sanchez
	Title	Feature Detectors and Feature Descriptors: Where We Are Now			Type	Report
	Year	2010	Publication	CVC Technical Report	Abbreviated Journal
	Volume	154	Issue		Pages
	Keywords
	Abstract	Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference
	Notes	MV;SIAI			Approved	no
	Call Number	Admin @ si @ BVS2010; IAM @ iam @ BVS2010			Serial	1348
Permanent link to this record



	Author	Lluis Pere de las Heras
	Title	Syntactic Model for Semantic Document Analysis			Type	Report
	Year	2010	Publication	CVC Technical Report	Abbreviated Journal
	Volume	158	Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ Per2010			Serial	1350
Permanent link to this record