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Author |
Antonio Lopez; Jiaolong Xu; Jose Luis Gomez; David Vazquez; German Ros |
![download PDF file pdf](img/file_PDF.gif)
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Title |
From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example |
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Book Chapter |
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2017 |
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Domain Adaptation in Computer Vision Applications |
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13 |
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243-258 |
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Domain Adaptation |
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Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical bottleneck. The reason is that, at least, we have to frame object examples with bounding boxes in thousands of images. A priori, the more complex the model is regarding its number of parameters, the more annotated examples are required. This annotation task is performed by human oracles, which ends up in inaccuracies and errors in the annotations (aka ground truth) since the task is inherently very cumbersome and sometimes ambiguous. As an alternative we have pioneered the use of virtual worlds for collecting such annotations automatically and with high precision. However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA). In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA. As a use case, we address the challenge of vehicle detection for driver assistance, using different publicly available virtual-world data. While doing so, we investigate questions such as: how does the domain gap behave due to virtual-vs-real data with respect to dominant object appearance per domain, as well as the role of photo-realism in the virtual world. |
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Springer |
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Gabriela Csurka |
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ADAS; 600.085; 601.223; 600.076; 600.118 |
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ADAS @ adas @ LXG2017 |
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2872 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Subtle Facial Expression Recognition in Still Images and Videos |
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Book Chapter |
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2011 |
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Advances in Face Image Analysis: Techniques and Technologies |
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14 |
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259-277 |
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This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). |
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IGI-Global |
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New York, USA |
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Yu-Jin Zhang |
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978-1-6152-0991-0 |
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OR;MV |
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Admin @ si @ DoR2011 |
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1751 |
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Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus |
![download PDF file pdf](img/file_PDF.gif)
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Color Naming |
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2012 |
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Color in Computer Vision: Fundamentals and Applications |
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17 |
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287-317 |
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John Wiley & Sons, Ltd. |
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Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek |
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CIC |
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Admin @ si @ WBV2012 |
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2063 |
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Author |
Josep Llados; Gemma Sanchez; Enric Marti |
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Title |
A string based method to recognize symbols and structural textures in architectural plans |
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Book Chapter |
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Year |
1998 |
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Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers |
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LNCS |
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1389 |
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1998 |
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91-103 |
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This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion. |
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Springer Link |
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LNCS |
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DAG; IAM |
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IAM @ iam @ SLE1998 |
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1573 |
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Author |
Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca |
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Title |
Beyond the Static Camera: Issues and Trends in Active Vision |
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2011 |
Publication |
Visual Analysis of Humans: Looking at People |
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2 |
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11-30 |
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Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems. |
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Springer London |
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Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal |
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978-0-85729-996-3 |
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ISE |
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Admin @ si @ AFX2011 |
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1814 |
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Author |
Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
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Title |
On the Design of Low Redundancy Error-Correcting Output Codes |
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2011 |
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Ensembles in Machine Learning Applications |
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373 |
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21-38 |
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The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers. |
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Springer Berlin Heidelberg |
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1860-949X |
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978-3-642-22909-1 |
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MILAB; OR;HuPBA;MV |
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Admin @ si @ BEB2011b |
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1886 |
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Author |
Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo |
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Title |
Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models |
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Book Chapter |
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2012 |
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Vision Robotics: Technologies for Machine Learning and Vision Applications |
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23-42 |
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Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis. |
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IGI-Global |
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MILAB;HuPBA |
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Admin @ si @ PIE2012 |
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2064 |
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Author |
Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis |
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Title |
Advances in Tracking and Recognition of Human Motion |
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2009 |
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Encyclopedia of Information Science and Technology |
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I |
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65–71 |
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ADAS |
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ADAS @ adas @ ASG2009 |
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1143 |
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Permanent link to this record |
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Author |
Josep Llados; Jaime Lopez-Krahe; Enric Marti |
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Title |
A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform |
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Book Chapter |
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1997 |
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Machine Vision and Applications |
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10 |
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3 |
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150-158 |
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Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition |
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Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input. |
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DAG;IAM |
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IAM @ iam @ LLM1997a |
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1566 |
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Author |
Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance |
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Book Chapter |
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2012 |
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Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence |
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384 |
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3 |
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87-95 |
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The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally. |
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Springer Berlin Heidelberg |
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1860-949X |
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978-3-642-24033-1 |
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ISE |
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Admin @ si @ BFR2012 |
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2062 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? |
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2014 |
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G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology |
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796 |
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3 |
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159-181 |
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β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model |
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Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists. |
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Springer Netherlands |
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0065-2598 |
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978-94-007-7422-3 |
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IAM; 600.075 |
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IAM @ iam @ RGG2014 |
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2197 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
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Title |
A Discriminative Non-Linear Manifold Learning Technique for Face Recognition |
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2011 |
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Informatics Engineering and Information Science |
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254 |
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6 |
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339-353 |
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In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance. |
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Springer Berlin Heidelberg |
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1865-0929 |
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978-3-642-25482-6 |
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ICIEIS |
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OR;MV |
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Admin @ si @ RaD2011 |
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1804 |
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Author |
Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Semantics of Human Behavior in Image Sequences |
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Book Chapter |
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Year |
2011 |
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Computer Analysis of Human Behavior |
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7 |
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151-182 |
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Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images. |
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Springer London |
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Albert Ali Salah; |
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978-0-85729-993-2 |
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ISE |
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Admin @ si @ SFR2011 |
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1810 |
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Author |
Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca |
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Title |
Exploiting Multimodal Interaction Techniques for Video-Surveillance |
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Book Chapter |
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2013 |
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Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library |
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48 |
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8 |
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135-151 |
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In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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ISE; 605.203; 600.049 |
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CGA2013 |
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2222 |
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Author |
David Geronimo; Angel Sappa; Antonio Lopez |
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Title |
Stereo-based Candidate Generation for Pedestrian Protection Systems |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Binocular Vision: Development, Depth Perception and Disorders |
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9 |
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189–208 |
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Pedestrian Detection |
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This chapter describes a stereo-based algorithm that provides candidate image windows to a latter 2D classification stage in an on-board pedestrian detection system. The proposed algorithm, which consists of three stages, is based on the use of both stereo imaging and scene prior knowledge (i.e., pedestrians are on the ground) to reduce the candidate searching space. First, a successful road surface fitting algorithm provides estimates on the relative ground-camera pose. This stage directs the search toward the road area thus avoiding irrelevant regions like the sky. Then, three different schemes are used to scan the estimated road surface with pedestrian-sized windows: (a) uniformly distributed through the road surface (3D); (b) uniformly distributed through the image (2D); (c) not uniformly distributed but according to a quadratic function (combined 2D-3D). Finally, the set of candidate windows is reduced by analyzing their 3D content. Experimental results of the proposed algorithm, together with statistics of searching space reduction are provided. |
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NOVA Publishers |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ GSL2010 |
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1301 |
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