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Author Andrew Nolan; Daniel Serrano; Aura Hernandez-Sabate; Daniel Ponsa; Antonio Lopez edit   pdf
openurl 
  Title Obstacle mapping module for quadrotors on outdoor Search and Rescue operations Type Conference Article
  Year 2013 Publication International Micro Air Vehicle Conference and Flight Competition Abbreviated Journal  
  Volume Issue Pages  
  Keywords UAV  
  Abstract Obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAV), due to their limited payload capacity to carry advanced sensors. Unlike larger vehicles, MAV can only carry light weight sensors, for instance a camera, which is our main assumption in this work. We explore passive monocular depth estimation and propose a novel method Position Aided Depth Estimation
(PADE). We analyse PADE performance and compare it against the extensively used Time To Collision (TTC). We evaluate the accuracy, robustness to noise and speed of three Optical Flow (OF) techniques, combined with both depth estimation methods. Our results show PADE is more accurate than TTC at depths between 0-12 meters and is less sensitive to noise. Our findings highlight the potential application of PADE for MAV to perform safe autonomous navigation in
unknown and unstructured environments.
 
  Address Toulouse; France; September 2013  
  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 IMAV  
  Notes (up) ADAS; 600.054; 600.057;IAM Approved no  
  Call Number Admin @ si @ NSH2013 Serial 2371  
Permanent link to this record
 

 
Author Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil edit   pdf
doi  isbn
openurl 
  Title Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging Type Book Chapter
  Year 2015 Publication Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal  
  Volume 9534 Issue Pages 69-79  
  Keywords  
  Abstract Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm.  
  Address Munich; Germany; January 2015  
  Corporate Author Thesis  
  Publisher Springer International Publishing 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 978-3-319-28711-9 Medium  
  Area Expedition Conference STACOM  
  Notes (up) ADAS; IAM; 600.075; 600.076; 600.060; 601.145 Approved no  
  Call Number Admin @ si @ KHM2015 Serial 2734  
Permanent link to this record
 

 
Author Joan Serrat; Enric Marti edit  openurl
  Title Elastic matching using interpolation splines Type Conference Article
  Year 1991 Publication IV Spanish Symposium of Pattern Recognition and image Analysis Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) ADAS;IAM; Approved no  
  Call Number IAM @ iam @ SMV1991 Serial 1651  
Permanent link to this record
 

 
Author Aura Hernandez-Sabate; Lluis Albarracin; Daniel Calvo; Nuria Gorgorio edit   pdf
openurl 
  Title EyeMath: Identifying Mathematics Problem Solving Processes in a RTS Video Game Type Conference Article
  Year 2016 Publication 5th International Conference Games and Learning Alliance Abbreviated Journal  
  Volume 10056 Issue Pages 50-59  
  Keywords Simulation environment; Automated Driving; Driver-Vehicle interaction  
  Abstract Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GALA  
  Notes (up) ADAS;IAM; Approved no  
  Call Number HAC2016 Serial 2864  
Permanent link to this record
 

 
Author Saad Minhas; Aura Hernandez-Sabate; Shoaib Ehsan; Katerine Diaz; Ales Leonardis; Antonio Lopez; Klaus McDonald Maier edit   pdf
openurl 
  Title LEE: A photorealistic Virtual Environment for Assessing Driver-Vehicle Interactions in Self-Driving Mode Type Conference Article
  Year 2016 Publication 14th European Conference on Computer Vision Workshops Abbreviated Journal  
  Volume 9915 Issue Pages 894-900  
  Keywords Simulation environment; Automated Driving; Driver-Vehicle interaction  
  Abstract Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical.  
  Address Amsterdam; The Netherlands; October 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECCVW  
  Notes (up) ADAS;IAM; 600.085; 600.076 Approved no  
  Call Number MHE2016 Serial 2865  
Permanent link to this record
 

 
Author Gemma Sanchez; Josep Llados; Enric Marti edit   pdf
openurl 
  Title A string-based method to recognize symbols and structural textures in architectural plans Type Conference Article
  Year 1997 Publication 2nd IAPR Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper deals with the recognition of symbols and struc- tural 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 clus- tering 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 simila- rity 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.  
  Address Nancy, France  
  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 (up) DAG; IAM Approved no  
  Call Number IAM @ iam @ SLE1997 Serial 1498  
Permanent link to this record
 

 
Author Josep Llados; Gemma Sanchez; Enric Marti edit   pdf
doi  openurl
  Title A string based method to recognize symbols and structural textures in architectural plans Type Book Chapter
  Year 1998 Publication Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers Abbreviated Journal LNCS  
  Volume 1389 Issue 1998 Pages 91-103  
  Keywords  
  Abstract 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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Link Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title LNCS Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) DAG; IAM Approved no  
  Call Number IAM @ iam @ SLE1998 Serial 1573  
Permanent link to this record
 

 
Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title A model for image generation and symbol recognition through the deformation of lineal shapes Type Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue 15 Pages 2857-2867  
  Keywords  
  Abstract We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Science Inc. Place of Publication New York, NY, USA Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0167-8655 ISBN Medium  
  Area Expedition Conference  
  Notes (up) DAG; IAM Approved no  
  Call Number IAM @ iam @ VAM2003 Serial 1653  
Permanent link to this record
 

 
Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti edit   pdf
url  doi
isbn  openurl
  Title Symbol recognition: current advances and perspectives Type Book Chapter
  Year 2002 Publication Graphics Recognition Algorithms And Applications Abbreviated Journal LNCS  
  Volume 2390 Issue Pages 104-128  
  Keywords  
  Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.  
  Address London, UK  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor Dorothea Blostein and Young- Bin Kwon  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 3-540-44066-6 Medium  
  Area Expedition Conference GREC  
  Notes (up) DAG; IAM; Approved no  
  Call Number IAM @ iam @ LVS2002 Serial 1572  
Permanent link to this record
 

 
Author Oriol Ramos Terrades; Albert Berenguel; Debora Gil edit   pdf
doi  openurl
  Title A Flexible Outlier Detector Based on a Topology Given by Graph Communities Type Journal Article
  Year 2022 Publication Big Data Research Abbreviated Journal BDR  
  Volume 29 Issue Pages 100332  
  Keywords Classification algorithms; Detection algorithms; Description of feature space local structure; Graph communities; Machine learning algorithms; Outlier detectors  
  Abstract Outlier detection is essential for optimal performance of machine learning methods and statistical predictive models. Their detection is especially determinant in small sample size unbalanced problems, since in such settings outliers become highly influential and significantly bias models. This particular experimental settings are usual in medical applications, like diagnosis of rare pathologies, outcome of experimental personalized treatments or pandemic emergencies. In contrast to population-based methods, neighborhood based local approaches compute an outlier score from the neighbors of each sample, are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. A main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters, like the number of neighbors.
This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world and synthetic data sets show that our approach outperforms, both, local and global strategies in multi and single view settings.
 
  Address August 28, 2022  
  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 (up) DAG; IAM; 600.140; 600.121; 600.139; 600.145; 600.159 Approved no  
  Call Number Admin @ si @ RBG2022a Serial 3718  
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