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Author Stefan Lonn; Petia Radeva; Mariella Dimiccoli edit  openurl
  Title (up) A picture is worth a thousand words but how to organize thousands of pictures? Type Miscellaneous
  Year 2018 Publication Arxiv Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract We live in a society where the large majority of the population has a camera-equipped smartphone. In addition, hard drives and cloud storage are getting cheaper and cheaper, leading to a tremendous growth in stored personal photos. Unlike photo collections captured by a digital camera, which typically are pre-processed by the user who organizes them into event-related folders, smartphone pictures are automatically stored in the cloud. As a consequence, photo collections captured by a smartphone are highly unstructured and because smartphones are ubiquitous, they present a larger variability compared to pictures captured by a digital camera. To solve the need of organizing large smartphone photo collections automatically, we propose here a new methodology for hierarchical photo organization into topics and topic-related categories. Our approach successfully estimates latent topics in the pictures by applying probabilistic Latent Semantic Analysis, and automatically assigns a name to each topic by relying on a lexical database. Topic-related categories are then estimated by using a set of topic-specific Convolutional Neuronal Networks. To validate our approach, we ensemble and make public a large dataset of more than 8,000 smartphone pictures from 10 persons. Experimental results demonstrate better user satisfaction with respect to state of the art solutions in terms of organization.  
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  Area Expedition Conference  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ LRD2018 Serial 3111  
Permanent link to this record
 

 
Author Gemma Sanchez; Ernest Valveny; Josep Llados; Joan Mas; N. Lozano edit  openurl
  Title (up) A platform to extract knowledge from graphic documents. Application to an architectural sketch understanding scenario Type Miscellaneous
  Year 2004 Publication Document Analysis Systems VI, S. Marinai, A. Dengel (Eds.) Lecture Notes in Computer Science, 3163:389–400 Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Springer-Verlag  
  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 DAG @ dag @ SVL2004 Serial 460  
Permanent link to this record
 

 
Author Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny edit  doi
isbn  openurl
  Title (up) A polar-based logo representation based on topological and colour features Type Conference Article
  Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 341–348  
  Keywords  
  Abstract In this paper, we propose a novel rotation and scale invariant method for colour logo retrieval and classification, which involves performing a simple colour segmentation and subsequently describing each of the resultant colour components based on a set of topological and colour features. A polar representation is used to represent the logo and the subsequent logo matching is based on Cyclic Dynamic Time Warping (CDTW). We also show how combining information about the global distribution of the logo components and their local neighbourhood using the Delaunay triangulation allows to improve the results. All experiments are performed on a dataset of 2500 instances of 100 colour logo images in different rotations and scales.  
  Address Boston; USA;  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-60558-773-8 Medium  
  Area Expedition Conference DAS  
  Notes DAG Approved no  
  Call Number DAG @ dag @ NKV2010 Serial 1436  
Permanent link to this record
 

 
Author Zhanwu Xiong edit  openurl
  Title (up) A Pompd Model for Active Camera Control Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 156 Issue Pages  
  Keywords  
  Abstract  
  Address  
  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 ISE Approved no  
  Call Number Admin @ si @ Xio2010 Serial 1356  
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Author Dennis G.Romero; Anselmo Frizera; Angel Sappa; Boris X. Vintimilla; Teodiano F.Bastos edit   pdf
url  doi
isbn  openurl
  Title (up) A predictive model for human activity recognition by observing actions and context Type Conference Article
  Year 2015 Publication Advanced Concepts for Intelligent Vision Systems, Proceedings of 16th International Conference, ACIVS 2015 Abbreviated Journal  
  Volume 9386 Issue Pages 323-333  
  Keywords  
  Abstract This paper presents a novel model to estimate human activities — a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach.  
  Address Catania; Italy; October 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 978-3-319-25902-4 Medium  
  Area Expedition Conference ACIVS  
  Notes ADAS; 600.076 Approved no  
  Call Number Admin @ si @ RFS2015 Serial 2661  
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Author Stefan Schurischuster; Beatriz Remeseiro; Petia Radeva; Martin Kampel edit  url
openurl 
  Title (up) A Preliminary Study of Image Analysis for Parasite Detection on Honey Bees Type Conference Article
  Year 2018 Publication 15th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 10882 Issue Pages 465-473  
  Keywords  
  Abstract Varroa destructor is a parasite harming bee colonies. As the worldwide bee population is in danger, beekeepers as well as researchers are looking for methods to monitor the health of bee hives. In this context, we present a preliminary study to detect parasites on bee videos by means of image analysis and machine learning techniques. For this purpose, each video frame is analyzed individually to extract bee image patches, which are then processed to compute image descriptors and finally classified into mite and no mite bees. The experimental results demonstrated the adequacy of the proposed method, which will be a perfect stepping stone for a further bee monitoring system.  
  Address Povoa de Varzim; Portugal; June 2018  
  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 ICIAR  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ SRR2018a Serial 3110  
Permanent link to this record
 

 
Author M. Olivera; Angel Sappa; Victor Santos edit  doi
openurl 
  Title (up) A probabilistic approach for color correction in image mosaicking applications Type Journal Article
  Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 14 Issue 2 Pages 508 - 523  
  Keywords Color correction; image mosaicking; color transfer; color palette mapping functions  
  Abstract Image mosaicking applications require both geometrical and photometrical registrations between the images that compose the mosaic. This paper proposes a probabilistic color correction algorithm for correcting the photometrical disparities. First, the image to be color corrected is segmented into several regions using mean shift. Then, connected regions are extracted using a region fusion algorithm. Local joint image histograms of each region are modeled as collections of truncated Gaussians using a maximum likelihood estimation procedure. Then, local color palette mapping functions are computed using these sets of Gaussians. The color correction is performed by applying those functions to all the regions of the image. An extensive comparison with ten other state of the art color correction algorithms is presented, using two different image pair data sets. Results show that the proposed approach obtains the best average scores in both data sets and evaluation metrics and is also the most robust to failures.  
  Address  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1057-7149 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; 600.076 Approved no  
  Call Number Admin @ si @ OSS2015b Serial 2554  
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Author Francisco Cruz; Oriol Ramos Terrades edit  openurl
  Title (up) A probabilistic framework for handwritten text line segmentation Type Miscellaneous
  Year 2018 Publication Arxiv Abbreviated Journal  
  Volume Issue Pages  
  Keywords Document Analysis; Text Line Segmentation; EM algorithm; Probabilistic Graphical Models; Parameter Learning  
  Abstract We successfully combine Expectation-Maximization algorithm and variational
approaches for parameter learning and computing inference on Markov random fields. This is a general method that can be applied to many computer
vision tasks. In this paper, we apply it to handwritten text line segmentation.
We conduct several experiments that demonstrate that our method deal with
common issues of this task, such as complex document layout or non-latin
scripts. The obtained results prove that our method achieve state-of-theart performance on different benchmark datasets without any particular fine
tuning step.
 
  Address  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ CrR2018 Serial 3253  
Permanent link to this record
 

 
Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
openurl 
  Title (up) A Product graph based method for dual subgraph matching applied to symbol spotting Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.
 
  Address Bethlehem; PA; USA; August 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 GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ DLB2013b Serial 2359  
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Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
doi  isbn
openurl 
  Title (up) A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 7-11  
  Keywords Product graph; Dual edge graph; Subgraph matching; Random walks; Graph kernel  
  Abstract Product graph has been shown as a way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. Here we focus on the two major limitations of the previous version of the algorithm: (1) spurious nodes and edges in the graph representation and (2) inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual edge graph representation on the original graph representing the graphical information and the product graph is computed between the dual edge graphs of the pattern graph and the target graph. The dual edge graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates the pair of similar edges of two operand graphs and exponentiating the adjacency matrix finds similar random walks of greater lengths. Nodes joining similar random walks between two graphs are found by combining different weighted exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ DLB2014 Serial 2698  
Permanent link to this record
 

 
Author Salvatore Tabbone; Josep Llados edit  openurl
  Title (up) A Propos de la Reconnaissance de Documents Graphiques: Synthese et Perspectives Type Conference Article
  Year 2007 Publication Traitement et Analyse de l’Information: Methodes et Applications Abbreviated Journal  
  Volume Issue Pages 247–258  
  Keywords  
  Abstract  
  Address Hammamet (Tunis)  
  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 TAIMA’07  
  Notes DAG Approved no  
  Call Number DAG @ dag @ TaL2007 Serial 890  
Permanent link to this record
 

 
Author M. Visani; Oriol Ramos Terrades; Salvatore Tabbone edit  doi
openurl 
  Title (up) A Protocol to Characterize the Descriptive Power and the Complementarity of Shape Descriptors Type Journal Article
  Year 2011 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 14 Issue 1 Pages 87-100  
  Keywords Document analysis; Shape descriptors; Symbol description; Performance characterization; Complementarity analysis  
  Abstract Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR’07, pp. 227–231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of measures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complementarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance characteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.  
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  Notes DAG; IF 1.091 Approved no  
  Call Number Admin @ si @VRT2011 Serial 1856  
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Author Maurizio Mencuccini; Jordi Martinez-Vilalta; Josep Piñol; Lasse Loepfe; Mireia Burnat ; Xavier Alvarez; Juan Camacho; Debora Gil edit   pdf
url  doi
openurl 
  Title (up) A quantitative and statistically robust method for the determination of xylem conduit spatial distribution Type Journal Article
  Year 2010 Publication American Journal of Botany Abbreviated Journal AJB  
  Volume 97 Issue 8 Pages 1247-1259  
  Keywords Geyer; hydraulic conductivity; point pattern analysis; Ripley; Spatstat; vessel clusters; xylem anatomy; xylem network  
  Abstract Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. * Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. * Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. * Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns.  
  Address  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ MMG2010 Serial 1623  
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Author Guillermo Torres; Debora Gil; Antonio Rosell; Sonia Baeza; Carles Sanchez edit  openurl
  Title (up) A radiomic biopsy for virtual histology of pulmonary nodules Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Pòster  
  Address Cartagena de Indias; Colombia; April 2023  
  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 ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ TGR2023b Serial 3954  
Permanent link to this record
 

 
Author Gerard Canal; Sergio Escalera; Cecilio Angulo edit   pdf
doi  openurl
  Title (up) A Real-time Human-Robot Interaction system based on gestures for assistive scenarios Type Journal Article
  Year 2016 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU  
  Volume 149 Issue Pages 65-77  
  Keywords Gesture recognition; Human Robot Interaction; Dynamic Time Warping; Pointing location estimation  
  Abstract Natural and intuitive human interaction with robotic systems is a key point to develop robots assisting people in an easy and effective way. In this paper, a Human Robot Interaction (HRI) system able to recognize gestures usually employed in human non-verbal communication is introduced, and an in-depth study of its usability is performed. The system deals with dynamic gestures such as waving or nodding which are recognized using a Dynamic Time Warping approach based on gesture specific features computed from depth maps. A static gesture consisting in pointing at an object is also recognized. The pointed location is then estimated in order to detect candidate objects the user may refer to. When the pointed object is unclear for the robot, a disambiguation procedure by means of either a verbal or gestural dialogue is performed. This skill would lead to the robot picking an object in behalf of the user, which could present difficulties to do it by itself. The overall system — which is composed by a NAO and Wifibot robots, a KinectTM v2 sensor and two laptops — is firstly evaluated in a structured lab setup. Then, a broad set of user tests has been completed, which allows to assess correct performance in terms of recognition rates, easiness of use and response times.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier B.V. 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 HuPBA;MILAB; Approved no  
  Call Number Admin @ si @ CEA2016 Serial 2768  
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