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Author Pierluigi Casale; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title (down) Personalization and User Verification in Wearable Systems using Biometric Walking Patterns Type Journal Article
  Year 2012 Publication Personal and Ubiquitous Computing Abbreviated Journal PUC  
  Volume 16 Issue 5 Pages 563-580  
  Keywords  
  Abstract In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1617-4909 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPR2012 Serial 1706  
Permanent link to this record
 

 
Author Xavier Otazu edit   pdf
url  openurl
  Title (down) Perceptual tone-mapping operator based on multiresolution contrast decomposition Type Abstract
  Year 2012 Publication Perception Abbreviated Journal PER  
  Volume 41 Issue Pages 86  
  Keywords  
  Abstract Tone-mapping operators (TMO) are used to display high dynamic range(HDR) images in low dynamic range (LDR) displays. Many computational and biologically inspired approaches have been used in the literature, being many of them based on multiresolution decompositions. In this work, a simple two stage model for TMO is presented. The first stage is a novel multiresolution contrast decomposition, which is inspired in a pyramidal contrast decomposition (Peli, 1990 Journal of the Optical Society of America7(10), 2032-2040).
This novel multiresolution decomposition represents the Michelson contrast of the image at different spatial scales. This multiresolution contrast representation, applied on the intensity channel of an opponent colour decomposition, is processed by a non-linear saturating model of V1 neurons (Albrecht et al, 2002 Journal ofNeurophysiology 88(2) 888-913). This saturation model depends on the visual frequency, and it has been modified in order to include information from the extended Contrast Sensitivity Function (e-CSF) (Otazu et al, 2010 Journal ofVision10(12) 5).
A set of HDR images in Radiance RGBE format (from CIS HDR Photographic Survey and Greg Ward database) have been used to test the model, obtaining a set of LDR images. The resulting LDR images do not show the usual halo or color modification artifacts.
 
  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 0301-0066 ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ Ota2012 Serial 2179  
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Author Lluis Gomez edit   pdf
openurl 
  Title (down) Perceptual Organization for Text Extraction in Natural Scenes Type Report
  Year 2012 Publication CVC Technical Report Abbreviated Journal  
  Volume 173 Issue Pages  
  Keywords  
  Abstract  
  Address Bellaterra  
  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 DAG Approved no  
  Call Number Admin @ si @ Gom2012 Serial 2309  
Permanent link to this record
 

 
Author Ivo Everts; Jan van Gemert; Theo Gevers edit  doi
isbn  openurl
  Title (down) Per-patch Descriptor Selection using Surface and Scene Properties Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal  
  Volume 7577 Issue VI Pages 172-186  
  Keywords  
  Abstract Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool.  
  Address Florence, Italy  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-33782-6 Medium  
  Area Expedition Conference ECCV  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ EGG2012 Serial 2023  
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Author Javier Marin; David Geronimo; David Vazquez; Antonio Lopez edit   pdf
isbn  openurl
  Title (down) 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 Diego Cheda; Daniel Ponsa; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title (down) Pedestrian Candidates Generation using Monocular Cues Type Conference Article
  Year 2012 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal  
  Volume Issue Pages 7-12  
  Keywords pedestrian detection  
  Abstract Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached.  
  Address  
  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 1931-0587 ISBN 978-1-4673-2119-8 Medium  
  Area Expedition Conference IV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d Serial 2013  
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Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  isbn
openurl 
  Title (down) Out-of-Sample Embedding by Sparse Representation Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 336-344  
  Keywords  
  Abstract A critical aspect of non-linear dimensionality reduction techniques is represented by the construction of the adjacency graph. The difficulty resides in finding the optimal parameters, a process which, in general, is heuristically driven. Recently, sparse representation has been proposed as a non-parametric solution to overcome this problem. In this paper, we demonstrate that this approach not only serves for the graph construction, but also represents an efficient and accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. Experimental results conducted on some challenging datasets confirmed the robustness of our approach and its superiority when compared to existing techniques.  
  Address  
  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 978-3-642-34165-6 Medium  
  Area Expedition Conference SSPR&SPR  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RaD2012c Serial 2175  
Permanent link to this record
 

 
Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title (down) Optimal Medial Surface Generation for Anatomical Volume Representations Type Book Chapter
  Year 2012 Publication Abdominal Imaging. Computational and Clinical Applications Abbreviated Journal LNCS  
  Volume 7601 Issue Pages 265-273  
  Keywords Medial surface representation; volume reconstruction  
  Abstract Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial
surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction.
This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology.
 
  Address Nice, France  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW.  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-33611-9 Medium  
  Area Expedition Conference STACOM  
  Notes IAM Approved no  
  Call Number IAM @ iam @ VGG2012b Serial 1988  
Permanent link to this record
 

 
Author Naveen Onkarappa; Sujay M. Veerabhadrappa; Angel Sappa edit  doi
isbn  openurl
  Title (down) Optical Flow in Onboard Applications: A Study on the Relationship Between Accuracy and Scene Texture Type Conference Article
  Year 2012 Publication 4th International Conference on Signal and Image Processing Abbreviated Journal  
  Volume 221 Issue Pages 257-267  
  Keywords  
  Abstract Optical flow has got a major role in making advanced driver assistance systems (ADAS) a reality. ADAS applications are expected to perform efficiently in all kinds of environments, those are highly probable, that one can drive the vehicle in different kinds of roads, times and seasons. In this work, we study the relationship of optical flow with different roads, that is by analyzing optical flow accuracy on different road textures. Texture measures such as TeX , TeX and TeX are evaluated for this purpose. Further, the relation of regularization weight to the flow accuracy in the presence of different textures is also analyzed. Additionally, we present a framework to generate synthetic sequences of different textures in ADAS scenarios with ground-truth optical flow.  
  Address Coimbatore, India  
  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 1876-1100 ISBN 978-81-322-0996-6 Medium  
  Area Expedition Conference ICSIP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OVS2012 Serial 2356  
Permanent link to this record
 

 
Author R. de Nijs; Sebastian Ramos; Gemma Roig; Xavier Boix; Luc Van Gool; K. Kühnlenz. edit   pdf
openurl 
  Title (down) On-line Semantic Perception Using Uncertainty Type Conference Article
  Year 2012 Publication International Conference on Intelligent Robots and Systems Abbreviated Journal IROS  
  Volume Issue Pages 4185-4191  
  Keywords Semantic Segmentation  
  Abstract Visual perception capabilities are still highly unreliable in unconstrained settings, and solutions might not beaccurate in all regions of an image. Awareness of the uncertainty of perception is a fundamental requirement for proper high level decision making in a robotic system. Yet, the uncertainty measure is often sacrificed to account for dependencies between object/region classifiers. This is the case of Conditional Random Fields (CRFs), the success of which stems from their ability to infer the most likely world configuration, but they do not directly allow to estimate the uncertainty of the solution. In this paper, we consider the setting of assigning semantic labels to the pixels of an image sequence. Instead of using a CRF, we employ a Perturb-and-MAP Random Field, a recently introduced probabilistic model that allows performing fast approximate sampling from its probability density function. This allows to effectively compute the uncertainty of the solution, indicating the reliability of the most likely labeling in each region of the image. We report results on the CamVid dataset, a standard benchmark for semantic labeling of urban image sequences. In our experiments, we show the benefits of exploiting the uncertainty by putting more computational effort on the regions of the image that are less reliable, and use more efficient techniques for other regions, showing little decrease of performance  
  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 IROS  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ NRR2012 Serial 2378  
Permanent link to this record
 

 
Author Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta edit   pdf
doi  openurl
  Title (down) On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents Type Journal Article
  Year 2012 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 26 Issue 5 Pages 1263002-126027  
  Keywords Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025  
  Abstract 0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images.
 
  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 DAG Approved no  
  Call Number Admin @ si @ LRF2012 Serial 2128  
Permanent link to this record
 

 
Author Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title (down) On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 135-143  
  Keywords  
  Abstract Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Berlag, Berlin Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-34165-6 Medium  
  Area Expedition Conference SSPR&SPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ GVB2012c Serial 2167  
Permanent link to this record
 

 
Author Murad Al Haj; Jordi Gonzalez; Larry S. Davis edit  doi
isbn  openurl
  Title (down) On Partial Least Squares in Head Pose Estimation: How to simultaneously deal with misalignment Type Conference Article
  Year 2012 Publication 25th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2602-2609  
  Keywords  
  Abstract Head pose estimation is a critical problem in many computer vision applications. These include human computer interaction, video surveillance, face and expression recognition. In most prior work on heads pose estimation, the positions of the faces on which the pose is to be estimated are specified manually. Therefore, the results are reported without studying the effect of misalignment. We propose a method based on partial least squares (PLS) regression to estimate pose and solve the alignment problem simultaneously. The contributions of this paper are two-fold: 1) we show that the kernel version of PLS (kPLS) achieves better than state-of-the-art results on the estimation problem and 2) we develop a technique to reduce misalignment based on the learned PLS factors.  
  Address Providence, Rhode Island  
  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 ISE Approved no  
  Call Number Admin @ si @ HGD2012 Serial 2029  
Permanent link to this record
 

 
Author David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha edit   pdf
doi  isbn
openurl 
  Title (down) On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts Type Conference Article
  Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages 763-768  
  Keywords document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding  
  Abstract he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20%  
  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 Admin @ si @ FLF2012 Serial 2200  
Permanent link to this record
 

 
Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title (down) Non-Rigid Shape Registration: A Single Linear Least Squares Framework Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal  
  Volume 7578 Issue Pages 264-277  
  Keywords  
  Abstract This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided.  
  Address Florencia  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-33785-7 Medium  
  Area Expedition Conference ECCV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RoS2012a Serial 2158  
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