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	Author	Alejandro Gonzalez Alzate
	Title	Evaluation of spatiotemporal descriptors for pedestrian detection in video sequences			Type	Report
	Year	2011	Publication	CVC Technical Report	Abbreviated Journal
	Volume	166	Issue		Pages
	Keywords
	Abstract
	Address	Bellaterra (Spain)
	Corporate Author	Computer Vision Center			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	ADAS			Approved	no
	Call Number	Admin @ si @ Gon2011			Serial	1932
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	Author	Yainuvis Socarras
	Title	Image segmentation for improving pedestrian detection			Type	Report
	Year	2011	Publication	CVC Technical Report	Abbreviated Journal
	Volume	167	Issue		Pages
	Keywords
	Abstract
	Address	Bellaterra (Spain)
	Corporate Author	Computer Vision Center			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	ADAS;			Approved	no
	Call Number	Admin @ si @ Soc2011			Serial	1933
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	Author	Maria del Camp Davesa
	Title	Human action categorization in image sequences			Type	Report
	Year	2011	Publication	CVC Technical Report	Abbreviated Journal
	Volume	169	Issue		Pages
	Keywords
	Abstract
	Address	Bellaterra (Spain)
	Corporate Author	Computer Vision Center			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;CIC			Approved	no
	Call Number	Admin @ si @ Dav2011			Serial	1934
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	Author	Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez
	Title	Color Attributes for Object Detection			Type	Conference Article
	Year	2012	Publication	25th IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	3306-3313
	Keywords	pedestrian detection
	Abstract	State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification, leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape. In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe- art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods.
	Address	Providence; Rhode Island; USA;
	Corporate Author				Thesis
	Publisher	IEEE Xplore	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1063-6919	ISBN	978-1-4673-1226-4	Medium
	Area		Expedition		Conference	CVPR
	Notes	ADAS; CIC;			Approved	no
	Call Number	Admin @ si @ KRW2012			Serial	1935
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	Author	Monica Piñol
	Title	Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning			Type	Report
	Year	2010	Publication	CVC Technical Report	Abbreviated Journal
	Volume	162	Issue		Pages
	Keywords
	Abstract
	Address	Bellaterra (Barcelona)
	Corporate Author	Computer Vision Center			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	ADAS			Approved	no
	Call Number	Admin @ si @ Piñ2010			Serial	1936
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	Author	Mohammad Rouhani; Angel Sappa
	Title	Implicit Polynomial Representation through a Fast Fitting Error Estimation			Type	Journal Article
	Year	2012	Publication	IEEE Transactions on Image Processing	Abbreviated Journal	TIP
	Volume	21	Issue	4	Pages	2089-2098
	Keywords
	Abstract	Impact Factor This paper presents a simple distance estimation for implicit polynomial fitting. It is computed as the height of a simplex built between the point and the surface (i.e., a triangle in 2-D or a tetrahedron in 3-D), which is used as a coarse but reliable estimation of the orthogonal distance. The proposed distance can be described as a function of the coefficients of the implicit polynomial. Moreover, it is differentiable and has a smooth behavior . Hence, it can be used in any gradient-based optimization. In this paper, its use in a Levenberg-Marquardt framework is shown, which is particularly devoted for nonlinear least squares problems. The proposed estimation is a generalization of the gradient-based distance estimation, which is widely used in the literature. Experimental results, both in 2-D and 3-D data sets, are provided. Comparisons with state-of-the-art techniques are presented, showing the advantages of the proposed approach.
	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	1057-7149	ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ RoS2012b; ADAS @ adas @			Serial	1937
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	Author	Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds)
	Title	Graphics Recognition: Achievements, Challenges, and Evolution			Type	Book Whole
	Year	2010	Publication	8th International Workshop GREC 2009.	Abbreviated Journal
	Volume	6020	Issue		Pages
	Keywords
	Abstract
	Address	La Rochelle
	Corporate Author				Thesis
	Publisher	Springer Link	Place of Publication		Editor	Jean-Marc Ogier; Wenyin Liu; Josep Llados
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-13727-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ OLL2010			Serial	1976
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	Author	Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner
	Title	Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation			Type	Conference Article
	Year	2011	Publication	In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage	Abbreviated Journal
	Volume		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	CartoHerit
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ RRL2011b			Serial	1978
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	Author	Javier Marin; David Geronimo; David Vazquez; Antonio Lopez
	Title	Pedestrian Detection: Exploring Virtual Worlds			Type	Book Chapter
	Year	2012	Publication	Handbook of Pattern Recognition: Methods and Application	Abbreviated Journal
	Volume	5	Issue		Pages	145-162
	Keywords	Virtual worlds; Pedestrian Detection; Domain Adaptation
	Abstract	Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition.
	Address
	Corporate Author				Thesis
	Publisher	iConcept Press	Place of Publication		Editor
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-477554-82-1	Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ MGV2012			Serial	1979
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	Author	Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers
	Title	Improving HOG with Image Segmentation: Application to Human Detection			Type	Conference Article
	Year	2012	Publication	11th International Conference on Advanced Concepts for Intelligent Vision Systems	Abbreviated Journal
	Volume	7517	Issue		Pages	178-189
	Keywords	Segmentation; Pedestrian Detection
	Abstract	In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement. We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function.
	Address	Brno, Czech Republic
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	J. Blanc-Talon et al.
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-33139-8	Medium
	Area		Expedition		Conference	ACIVS
	Notes	ADAS;ISE			Approved	no
	Call Number	ADAS @ adas @ SLV2012			Serial	1980
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	Author	David Vazquez; Antonio Lopez; Daniel Ponsa
	Title	Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	3492 - 3495
	Keywords	Pedestrian Detection; Domain Adaptation; Virtual worlds
	Abstract	Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1).
	Address	Tsukuba Science City, Japan
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication	Tsukuba Science City, JAPAN	Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1051-4651	ISBN	978-1-4673-2216-4	Medium
	Area		Expedition		Conference	ICPR
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ VLP2012			Serial	1981
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	Author	Jon Almazan; Alicia Fornes; Ernest Valveny
	Title	A non-rigid appearance model for shape description and recognition			Type	Journal Article
	Year	2012	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	45	Issue	9	Pages	3105--3113
	Keywords	Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition
	Abstract	In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach.
	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	0031-3203	ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ AFV2012			Serial	1982
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	Author	Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny
	Title	A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection			Type	Conference Article
	Year	2012	Publication	13th International Conference on Frontiers in Handwriting Recognition	Abbreviated Journal
	Volume		Issue		Pages	453-458
	Keywords
	Abstract	In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.
	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	978-1-4673-2262-1	Medium
	Area		Expedition		Conference	ICFHR
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ AFF2012			Serial	1983
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	Author	Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny
	Title	Efficient Exemplar Word Spotting			Type	Conference Article
	Year	2012	Publication	23rd British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages	67.1- 67.11
	Keywords
	Abstract	In this paper we propose an unsupervised segmentation-free method for word spotting in document images. Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage.
	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	1-901725-46-4	Medium
	Area		Expedition		Conference	BMVC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ AGF2012			Serial	1984
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	Author	Ferran Poveda; Enric Marti; Debora Gil; Francesc Carreras; Manel Ballester
	Title	Helical Structure of Ventricular Anatomy by Diffusion Tensor Cardiac MR Tractography			Type	Journal Article
	Year	2012	Publication	Journal of American College of Cardiology	Abbreviated Journal	JACC
	Volume	5	Issue	7	Pages	754-755
	Keywords
	Abstract	It is widely accepted that myocardial fiber architecture plays a critical role in myocardial contractility and relaxation (1). However, there is a lack of consensus about the distribution of the myocardial fibers and their spatial arrangement in the left and right ventricles. An understanding of the cardiac architecture should benefit the ventricular functional assessment, left ventricular reconstructive surgery planning, or resynchronization therapy in heart failure. Researchers have proposed several conceptual models to describe the architecture of the heart, ranging from gross dissection to histological presentation. The cardiac mesh model (2) proposes that the myocytes are arranged longitudinally and radially change their angulation along the myocardial depth. By contrast, the helical ventricular myocardial model states that the ventricular myocardium is a continuous anatomical helical layout of myocardial fibers (1
	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	1936-878X	ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ PMG2012			Serial	1985
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