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	Author	David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin
	Title	Cool world: domain adaptation of virtual and real worlds for human detection using active learning			Type	Conference Article
	Year	2011	Publication	NIPS Domain Adaptation Workshop: Theory and Application	Abbreviated Journal	NIPS-DA
	Volume		Issue		Pages
	Keywords	Pedestrian Detection; Virtual; Domain Adaptation; Active Learning
	Abstract	Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity.
	Address	Granada, Spain
	Corporate Author				Thesis
	Publisher		Place of Publication	Granada, Spain	Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	DA-NIPS
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ VLP2011b			Serial	1756
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	Author	Mario Rojas; David Masip; Jordi Vitria
	Title	Predicting Dominance Judgements Automatically: A Machine Learning Approach.			Type	Conference Article
	Year	2011	Publication	IEEE International Workshop on Social Behavior Analysis	Abbreviated Journal
	Volume		Issue		Pages	939-944
	Keywords
	Abstract	The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task.
	Address	Santa Barbara, CA
	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	978-1-4244-9140-7	Medium
	Area		Expedition		Conference	SBA
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ RMV2011b			Serial	1760
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	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva
	Title	User Verification From Walking Activity. First Steps Towards a Personal Verification System			Type	Conference Article
	Year	2011	Publication	1st International Conference on Pervasive and Embedded Computing and Communication Systems	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Algarve, Portugal
	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	PECCS
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ CPR2011c			Serial	1762
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	Author	Jon Almazan; Alicia Fornes; Ernest Valveny
	Title	A Non-Rigid Feature Extraction Method for Shape Recognition			Type	Conference Article
	Year	2011	Publication	11th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	987-991
	Keywords
	Abstract	This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost.
	Address	Beijing; China; September 2011
	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	978-0-7695-4520-2	Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ AFV2011			Serial	1763
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	Author	Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez
	Title	A Coarse-to-fine Approach for fast Deformable Object Detection			Type	Conference Article
	Year	2011	Publication	IEEE conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	1353-1360
	Keywords
	Abstract
	Address	Colorado Springs; USA
	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	CVPR
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ PVG2011			Serial	1764
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	Author	Miguel Oliveira; Angel Sappa; V.Santos
	Title	Unsupervised Local Color Correction for Coarsely Registered Images			Type	Conference Article
	Year	2011	Publication	IEEE conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	201-208
	Keywords
	Abstract	The current paper proposes a new parametric local color correction technique. Initially, several color transfer functions are computed from the output of the mean shift color segmentation algorithm. Secondly, color influence maps are calculated. Finally, the contribution of every color transfer function is merged using the weights from the color influence maps. The proposed approach is compared with both global and local color correction approaches. Results show that our method outperforms the technique ranked first in a recent performance evaluation on this topic. Moreover, the proposed approach is computed in about one tenth of the time.
	Address	Colorado Springs
	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	1063-6919	ISBN	978-1-4577-0394-2	Medium
	Area		Expedition		Conference	CVPR
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ OSS2011; ADAS @ adas @			Serial	1766
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	Author	Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva
	Title	Automatic Key Frames Detection in Intravascular Ultrasound Sequences			Type	Conference Article
	Year	2011	Publication	In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events.
	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	CVII
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ CPB2011			Serial	1767
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	Author	Miguel Reyes; Jose Ramirez Moreno; Juan R Revilla; Petia Radeva; Sergio Escalera
	Title	ADiBAS: Sistema Multisensor de Adquisicion Automatica de Datos Corporales Objetivos, Robustos y Fiables para el Analisis de la Postura y el Movimiento			Type	Conference Article
	Year	2011	Publication	6th Congreso Iberoamericano de Tecnologia de Apoyo a la Discapacidad	Abbreviated Journal
	Volume		Issue		Pages	939-944
	Keywords
	Abstract	El análisis de la postura y del rango de movimiento son fundamentales para conocer la optimización del gesto y mejorar, de este modo, el rendimiento y la detección de posibles lesiones. Esta cuantificación es especialmente interesante en deportistas o en pacientes que presentan alguna lesión neurológica o del sistema musculo-esquelético, ya que permite conocer el proceso evolutivo de estos pacientes, evaluar la eficacia de la terapia aplicada y proponer, en caso necesario, una modificación del protocolo de tratamiento. En este trabajo presentamos un sistema automático que permite, mediante una tecnología no invasiva, la captación automática de marcadores LED situados sobre el paciente y su posterior análisis con el fin de mostrar al especialista datos objetivos que permitan un mejor soporte diagnóstico. También se describe un sistema analítico de la postura corporal sin marcadores, donde su ejecución durante secuencias dinámicas aporta un alto grado de naturalidad al paciente a la hora de realizar los ejercicios funcionales.
	Address	Palma de Mallorca
	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	IBERDISCAP
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ RRR2011			Serial	1768
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	Author	Xavier Perez Sala; Cecilio Angulo; Sergio Escalera
	Title	Biologically Inspired Path Execution Using SURF Flow in Robot Navigation			Type	Conference Article
	Year	2011	Publication	11th International Work Conference on Artificial Neural Networks	Abbreviated Journal
	Volume	II	Issue		Pages	581--588
	Keywords
	Abstract	An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo.
	Address	Malaga
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-21497-4	Medium
	Area		Expedition		Conference	IWANN
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ PAE2011b			Serial	1773
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	Author	Oscar Amoros; Sergio Escalera; Anna Puig
	Title	Adaboost GPU-based Classifier for Direct Volume Rendering			Type	Conference Article
	Year	2011	Publication	International Conference on Computer Graphics Theory and Applications	Abbreviated Journal
	Volume		Issue		Pages	215-219
	Keywords
	Abstract	In volume visualization, the voxel visibitity and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges.
	Address	Algarve, Portugal
	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	GRAPP
	Notes	MILAB; HuPBA			Approved	no
	Call Number	Admin @ si @ AEP2011			Serial	1774
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	Author	Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras
	Title	The IIIA30 MObile Robot Object Recognition Datset			Type	Conference Article
	Year	2011	Publication	11th Portuguese Robotics Open	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones.
	Address	Lisboa
	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	Robotica
	Notes	RV;ADAS			Approved	no
	Call Number	Admin @ si @ RAV2011			Serial	1777
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	Author	Joost Van de Weijer; Shida Beigpour
	Title	The Dichromatic Reflection Model: Future Research Directions and Applications			Type	Conference Article
	Year	2011	Publication	International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	dblp
	Abstract	The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability.
	Address	Algarve, Portugal
	Corporate Author				Thesis
	Publisher	SciTePress	Place of Publication		Editor	Mestetskiy, Leonid and Braz, José
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-989-8425-47-8	Medium
	Area		Expedition		Conference	VISIGRAPP
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ WeB2011			Serial	1778
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	Author	Koen E.A. van de Sande; Jasper Uilings; Theo Gevers; Arnold Smeulders
	Title	Segmentation as Selective Search for Object Recognition			Type	Conference Article
	Year	2011	Publication	13th IEEE International Conference on Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	1879-1886
	Keywords
	Abstract	For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt segmentation as a selective search by reconsidering segmentation: We propose to generate many approximate locations over few and precise object delineations because (1) an object whose location is never generated can not be recognised and (2) appearance and immediate nearby context are most effective for object recognition. Our method is class-independent and is shown to cover 96.7% of all objects in the Pascal VOC 2007 test set using only 1,536 locations per image. Our selective search enables the use of the more expensive bag-of-words method which we use to substantially improve the state-of-the-art by up to 8.5% for 8 out of 20 classes on the Pascal VOC 2010 detection challenge.
	Address	Barcelona
	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	1550-5499	ISBN	978-1-4577-1101-5	Medium
	Area		Expedition		Conference	ICCV
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ SUG2011			Serial	1780
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	Author	Shida Beigpour; Joost Van de Weijer
	Title	Object Recoloring Based on Intrinsic Image Estimation			Type	Conference Article
	Year	2011	Publication	13th IEEE International Conference in Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	327 - 334
	Keywords
	Abstract	Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods.
	Address	Barcelona
	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	1550-5499	ISBN	978-1-4577-1101-5	Medium
	Area		Expedition		Conference	ICCV
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ BeW2011			Serial	1781
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	Author	Mohammad Rouhani; Angel Sappa
	Title	Implicit B-Spline Fitting Using the 3L Algorithm			Type	Conference Article
	Year	2011	Publication	18th IEEE International Conference on Image Processing	Abbreviated Journal
	Volume		Issue		Pages	893-896
	Keywords
	Abstract
	Address	Brussels, Belgium
	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	ICIP
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ RoS2011a; ADAS @ adas @			Serial	1782
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