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Author Karel Paleček; David Geronimo; Frederic Lerasle edit  doi
isbn  openurl
  Title Pre-attention cues for person detection Type Conference Article
  Year 2012 Publication Cognitive Behavioural Systems, COST 2102 International Training School Abbreviated Journal  
  Volume Issue Pages 225-235  
  Keywords  
  Abstract Current state-of-the-art person detectors have been proven reliable and achieve very good detection rates. However, the performance is often far from real time, which limits their use to low resolution images only. In this paper, we deal with candidate window generation problem for person detection, i.e. we want to reduce the computational complexity of a person detector by reducing the number of regions that has to be evaluated. We base our work on Alexe’s paper [1], which introduced several pre-attention cues for generic object detection. We evaluate these cues in the context of person detection and show that their performance degrades rapidly for scenes containing multiple objects of interest such as pictures from urban environment. We extend this set by new cues, which better suits our class-specific task. The cues are designed to be simple and efficient, so that they can be used in the pre-attention phase of a more complex sliding window based person detector.  
  Address Dresden, Germany  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-34583-8 Medium  
  Area Expedition Conference COST-TS  
  Notes ADAS Approved no  
  Call Number Admin @ si @ PGL2012 Serial 2148  
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Author Joan Arnedo-Moreno; Agata Lapedriza edit  openurl
  Title Visualizing key authenticity: turning your face into your public key Type Conference Article
  Year 2010 Publication 6th China International Conference on Information Security and Cryptology Abbreviated Journal  
  Volume Issue Pages 605-618  
  Keywords  
  Abstract Biometric information has become a technology complementary to cryptography, allowing to conveniently manage cryptographic data. Two important needs are ful lled: rst of all, making such data always readily available, and additionally, making its legitimate owner easily identi able. In this work we propose a signature system which integrates face recognition biometrics with and identity-based signature scheme, so the user's face e ectively becomes his public key and system ID. Thus, other users may verify messages using photos of the claimed sender, providing a reasonable trade-o between system security and usability, as well as a much more straightforward public key authenticity and distribution process.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference Inscrypt  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ ArL2010c Serial 2149  
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Author Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras edit  doi
openurl 
  Title Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot Type Journal Article
  Year 2012 Publication Journal of Intelligent and Robotic Systems Abbreviated Journal JIRC  
  Volume 68 Issue 2 Pages 185-208  
  Keywords  
  Abstract This paper addresses visual object perception applied to mobile robotics. Being able to perceive household objects in unstructured environments is a key capability in order to make robots suitable to perform complex tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Netherlands Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0921-0296 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RAV2012 Serial 2150  
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Author Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva edit   pdf
doi  openurl
  Title Adaptable image cuts for motility inspection using WCE Type Journal Article
  Year 2013 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG  
  Volume 37 Issue 1 Pages 72-80  
  Keywords  
  Abstract The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; OR; 600.046; 605.203 Approved no  
  Call Number Admin @ si @ DSM2012 Serial 2151  
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Author Petia Radeva; Michal Drozdzal; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria edit   pdf
doi  isbn
openurl 
  Title Active labeling: Application to wireless endoscopy analysis Type Conference Article
  Year 2012 Publication High Performance Computing and Simulation, International Conference on Abbreviated Journal  
  Volume Issue Pages 174-181  
  Keywords  
  Abstract Today, robust learners trained in a real supervised machine learning application should count with a rich collection of positive and negative examples. Although in many applications, it is not difficult to obtain huge amount of data, labeling those data can be a very expensive process, especially when dealing with data of high variability and complexity. A good example of such cases are data from medical imaging applications where annotating anomalies like tumors, polyps, atherosclerotic plaque or informative frames in wireless endoscopy need highly trained experts. Building a representative set of training data from medical videos (e.g. Wireless Capsule Endoscopy) means that thousands of frames to be labeled by an expert. It is quite normal that data in new videos come different and thus are not represented by the training set. In this paper, we review the main approaches on active learning and illustrate how active learning can help to reduce expert effort in constructing the training sets. We show that applying active learning criteria, the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of Wireless Capsule Endoscopy video containing more than 30000 frames each one with less than 100 expert ”clicks”.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4673-2359-8 Medium  
  Area Expedition Conference HPCS  
  Notes MILAB; OR;MV Approved no  
  Call Number Admin @ si @ RDS2012 Serial 2152  
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Author Jose Carlos Rubio; Joan Serrat; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Video Co-segmentation Type Conference Article
  Year 2012 Publication 11th Asian Conference on Computer Vision Abbreviated Journal  
  Volume 7725 Issue Pages 13-24  
  Keywords  
  Abstract Segmentation of a single image is in general a highly underconstrained problem. A frequent approach to solve it is to somehow provide prior knowledge or constraints on how the objects of interest look like (in terms of their shape, size, color, location or structure). Image co-segmentation trades the need for such knowledge for something much easier to obtain, namely, additional images showing the object from other viewpoints. Now the segmentation problem is posed as one of differentiating the similar object regions in all the images from the more varying background. In this paper, for the first time, we extend this approach to video segmentation: given two or more video sequences showing the same object (or objects belonging to the same class) moving in a similar manner, we aim to outline its region in all the frames. In addition, the method works in an unsupervised manner, by learning to segment at testing time. We compare favorably with two state-of-the-art methods on video segmentation and report results on benchmark videos.  
  Address Daejeon, Korea  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-37443-2 Medium  
  Area Expedition Conference ACCV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RSL2012d Serial 2153  
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Author Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo edit   pdf
doi  openurl
  Title Multispectral Image Feature Points Type Journal Article
  Year 2012 Publication Sensors Abbreviated Journal SENS  
  Volume 12 Issue 9 Pages 12661-12672  
  Keywords multispectral image descriptor; color and infrared images; feature point descriptor  
  Abstract Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ ABL2012 Serial 2154  
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Author Fernando Barrera; Felipe Lumbreras; Angel Sappa edit   pdf
doi  openurl
  Title Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation Type Journal Article
  Year 2012 Publication IEEE Journal of Selected Topics in Signal Processing Abbreviated Journal J-STSP  
  Volume 6 Issue 5 Pages 437-446  
  Keywords  
  Abstract This paper proposes an imaging system for computing sparse depth maps from multispectral images. A special stereo head consisting of an infrared and a color camera defines the proposed multimodal acquisition system. The cameras are rigidly attached so that their image planes are parallel. Details about the calibration and image rectification procedure are provided. Sparse disparity maps are obtained by the combined use of mutual information enriched with gradient information. The proposed approach is evaluated using a Receiver Operating Characteristics curve. Furthermore, a multispectral dataset, color and infrared images, together with their corresponding ground truth disparity maps, is generated and used as a test bed. Experimental results in real outdoor scenarios are provided showing its viability and that the proposed approach is not restricted to a specific domain.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1932-4553 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ BLS2012b Serial 2155  
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Author Cristhian Aguilera; M.Ramos; Angel Sappa edit   pdf
doi  isbn
openurl 
  Title Simulated Annealing: A Novel Application of Image Processing in the Wood Area Type Book Chapter
  Year 2012 Publication Simulated Annealing – Advances, Applications and Hybridizations Abbreviated Journal  
  Volume Issue Pages 91-104  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Marcos de Sales Guerra Tsuzuki  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-953-51-0710-1 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ ARS2012 Serial 2156  
Permanent link to this record
 

 
Author Monica Piñol; Angel Sappa; Ricardo Toledo edit   pdf
doi  isbn
openurl 
  Title MultiTable Reinforcement for Visual Object Recognition Type Conference Article
  Year 2012 Publication 4th International Conference on Signal and Image Processing Abbreviated Journal  
  Volume 221 Issue Pages 469-480  
  Keywords  
  Abstract This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach.  
  Address Coimbatore, India  
  Corporate Author Thesis  
  Publisher Springer India Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title LNCS  
  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 @ PST2012 Serial 2157  
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Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title 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 (up) 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  
Permanent link to this record
 

 
Author Miguel Oliveira; V.Santos; Angel Sappa edit  openurl
  Title Short term path planning using a multiple hypothesis evaluation approach for an autonomous driving competition Type Conference Article
  Year 2012 Publication IEEE 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles 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 (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference PPNIV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OSS2012c Serial 2159  
Permanent link to this record
 

 
Author David Geronimo; Joan Serrat; Antonio Lopez; Ramon Baldrich edit   pdf
doi  openurl
  Title Traffic sign recognition for computer vision project-based learning Type Journal Article
  Year 2013 Publication IEEE Transactions on Education Abbreviated Journal T-EDUC  
  Volume 56 Issue 3 Pages 364-371  
  Keywords traffic signs  
  Abstract This paper presents a graduate course project on computer vision. The aim of the project is to detect and recognize traffic signs in video sequences recorded by an on-board vehicle camera. This is a demanding problem, given that traffic sign recognition is one of the most challenging problems for driving assistance systems. Equally, it is motivating for the students given that it is a real-life problem. Furthermore, it gives them the opportunity to appreciate the difficulty of real-world vision problems and to assess the extent to which this problem can be solved by modern computer vision and pattern classification techniques taught in the classroom. The learning objectives of the course are introduced, as are the constraints imposed on its design, such as the diversity of students' background and the amount of time they and their instructors dedicate to the course. The paper also describes the course contents, schedule, and how the project-based learning approach is applied. The outcomes of the course are discussed, including both the students' marks and their personal feedback.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0018-9359 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; CIC Approved no  
  Call Number Admin @ si @ GSL2013; ADAS @ adas @ Serial 2160  
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Author Joan Serrat; Felipe Lumbreras; Antonio Lopez edit   pdf
doi  openurl
  Title Cost estimation of custom hoses from STL files and CAD drawings Type Journal Article
  Year 2013 Publication Computers in Industry Abbreviated Journal COMPUTIND  
  Volume 64 Issue 3 Pages 299-309  
  Keywords On-line quotation; STL format; Regression; Gaussian process  
  Abstract We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; 600.057; 600.054; 605.203 Approved no  
  Call Number Admin @ si @ SLL2013; ADAS @ adas @ Serial 2161  
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Author Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title Automatic Non-Rigid Temporal Alignment of IVUS Sequences Type Conference Article
  Year 2012 Publication 15th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 1 Issue Pages 642-650  
  Keywords  
  Abstract Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability.  
  Address Nice, France  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-33414-6 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB Approved no  
  Call Number Admin @ si @ ABC2012 Serial 2168  
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