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Author | Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez | ||||
Title | Stereo Matching using SGM on the GPU | Type | Report | ||
Year | 2016 | Publication | Programming and Tuning Massively Parallel Systems | Abbreviated Journal | PUMPS |
Volume | Issue | Pages | |||
Keywords | CUDA; Stereo; Autonomous Vehicle | ||||
Abstract | Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. | ||||
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Area | Expedition | Conference | PUMPS | ||
Notes | ADAS; 600.085; 600.087; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ HCE2016b | Serial | 2776 | ||
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Author | Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig | ||||
Title | Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis | Type | Book Chapter | ||
Year | 2015 | Publication | Artificial Intelligence Research and Development | Abbreviated Journal | |
Volume | 277 | Issue | Pages | 247 - 256 | |
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Abstract | Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms. | ||||
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Publisher | IOS Press | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Frontiers in Artificial Intelligence and Applications | Abbreviated Series Title | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @TVR2015 | Serial | 2780 | ||
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Author | E. Tavalera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva | ||||
Title | Regularized Clustering for Egocentric Video Segmentation | Type | Book Chapter | ||
Year | 2015 | Publication | Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | Issue | Pages | 327-336 | ||
Keywords | Temporal video segmentation ; Egocentric videos ; Clustering | ||||
Abstract | In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energyminimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate techniques in an energy-minimization framework that serves disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. | ||||
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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 | ISBN | 978-3-319-19390-8 | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @TDB2015a | Serial | 2781 | ||
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Author | Mariella Dimiccoli | ||||
Title | Fundamentals of cone regression | Type | Journal | ||
Year | 2016 | Publication | Journal of Statistics Surveys | Abbreviated Journal | |
Volume | 10 | Issue | Pages | 53-99 | |
Keywords | cone regression; linear complementarity problems; proximal operators. | ||||
Abstract | Cone regression is a particular case of quadratic programming that minimizes a weighted sum of squared residuals under a set of linear inequality constraints. Several important statistical problems such as isotonic, concave regression or ANOVA under partial orderings, just to name a few, can be considered as particular instances of the cone regression problem. Given its relevance in Statistics, this paper aims to address the fundamentals of cone regression from a theoretical and practical point of view. Several formulations of the cone regression problem are considered and, focusing on the particular case of concave regression as an example, several algorithms are analyzed and compared both qualitatively and quantitatively through numerical simulations. Several improvements to enhance numerical stability and bound the computational cost are proposed. For each analyzed algorithm, the pseudo-code and its corresponding code in Matlab are provided. The results from this study demonstrate that the choice of the optimization approach strongly impacts the numerical performances. It is also shown that methods are not currently available to solve efficiently cone regression problems with large dimension (more than many thousands of points). We suggest further research to fill this gap by exploiting and adapting classical multi-scale strategy to compute an approximate solution. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 1935-7516 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @Dim2016a | Serial | 2783 | ||
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Author | Maria Oliver; Gloria Haro; Mariella Dimiccoli; Baptiste Mazin; Coloma Ballester | ||||
Title | A computational model of amodal completion | Type | Conference Article | ||
Year | 2016 | Publication | SIAM Conference on Imaging Science | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | This paper presents a computational model to recover the most likely interpretation of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler's elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler's elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling. | ||||
Address | Albuquerque; New Mexico; USA; May 2016 | ||||
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Area | Expedition | Conference | IS | ||
Notes | MILAB; 601.235 | Approved | no | ||
Call Number | Admin @ si @OHD2016a | Serial | 2788 | ||
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Author | G. de Oliveira; A. Cartas; Marc Bolaños; Mariella Dimiccoli; Xavier Giro; Petia Radeva | ||||
Title | LEMoRe: A Lifelog Engine for Moments Retrieval at the NTCIR-Lifelog LSAT Task | Type | Conference Article | ||
Year | 2016 | Publication | 12th NTCIR Conference on Evaluation of Information Access Technologies | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Semantic image retrieval from large amounts of egocentric visual data requires to leverage powerful techniques for filling in the semantic gap. This paper introduces LEMoRe, a Lifelog Engine for Moments Retrieval, developed in the context of the Lifelog Semantic Access Task (LSAT) of the the NTCIR-12 challenge and discusses its performance variation on different trials. LEMoRe integrates classical image descriptors with high-level semantic concepts extracted by Convolutional Neural Networks (CNN), powered by a graphic user interface that uses natural language processing. Although this is just a first attempt towards interactive image retrieval from large egocentric datasets and there is a large room for improvement of the system components and the user interface, the structure of the system itself and the way the single components cooperate are very promising. | ||||
Address | Tokyo; Japan; June 2016 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | NTCIR | ||
Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @OCB2016 | Serial | 2789 | ||
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Author | G. de Oliveira; Mariella Dimiccoli; Petia Radeva | ||||
Title | Egocentric Image Retrieval With Deep Convolutional Neural Networks | Type | Conference Article | ||
Year | 2016 | Publication | 19th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
Volume | Issue | Pages | 71-76 | ||
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Address | Barcelona; Spain; October 2016 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CCIA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ODR2016 | Serial | 2790 | ||
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Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
Title | With whom do I interact with? Social interaction detection in egocentric photo-streams | Type | Conference Article | ||
Year | 2016 | Publication | 23rd International Conference on Pattern Recognition | Abbreviated Journal | |
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Abstract | Given a user wearing a low frame rate wearable camera during a day, this work aims to automatically detect the moments when the user gets engaged into a social interaction solely by reviewing the automatically captured photos by the worn camera. The proposed method, inspired by the sociological concept of F-formation, exploits distance and orientation of the appearing individuals -with respect to the user- in the scene from a bird-view perspective. As a result, the interaction pattern over the sequence can be understood as a two-dimensional time series that corresponds to the temporal evolution of the distance and orientation features over time. A Long-Short Term Memory-based Recurrent Neural Network is then trained to classify each time series. Experimental evaluation over a dataset of 30.000 images has shown promising results on the proposed method for social interaction detection in egocentric photo-streams. | ||||
Address | Cancun; Mexico; December 2016 | ||||
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Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | ICPR | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ADR2016a | Serial | 2791 | ||
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Author | Mariella Dimiccoli; Petia Radeva | ||||
Title | Lifelogging in the era of outstanding digitization | Type | Conference Article | ||
Year | 2015 | Publication | International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage | Abbreviated Journal | |
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Abstract | In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. | ||||
Address | Verliko Tarmovo; Bulgaria; September 2015 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DiPP | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @DiR2016 | Serial | 2792 | ||
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Author | Aniol Lidon; Xavier Giro; Marc Bolaños; Petia Radeva; Markus Seidl; Matthias Zeppelzauer | ||||
Title | UPC-UB-STP @ MediaEval 2015 diversity task: iterative reranking of relevant images | Type | Conference Article | ||
Year | 2015 | Publication | 2015 MediaEval Retrieving Diverse Images Task | Abbreviated Journal | |
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Abstract | This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task. The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity. | ||||
Address | Wurzen; Germany; September 2015 | ||||
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Area | Expedition | Conference | MediaEval | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @LGB2016 | Serial | 2793 | ||
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Author | Jose Manuel Alvarez; Theo Gevers; Antonio Lopez | ||||
Title | Evaluating Color Representation for Online Road Detection | Type | Conference Article | ||
Year | 2013 | Publication | ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars | Abbreviated Journal | |
Volume | Issue | Pages | 594-595 | ||
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Abstract | Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired using an on-board camera in different real-driving situations. |
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Area | Expedition | Conference | CVVT:E2M | ||
Notes | ADAS;ISE | Approved | no | ||
Call Number | Admin @ si @ AGL2013 | Serial | 2794 | ||
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Author | Y. Patel; Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas | ||||
Title | Dynamic Lexicon Generation for Natural Scene Images | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 395-410 | ||
Keywords | scene text; photo OCR; scene understanding; lexicon generation; topic modeling; CNN | ||||
Abstract | Many scene text understanding methods approach the endtoend recognition problem from a word-spotting perspective and take huge benet from using small per-image lexicons. Such customized lexicons are normally assumed as given and their source is rarely discussed.
In this paper we propose a method that generates contextualized lexicons for scene images using only visual information. For this, we exploit the correlation between visual and textual information in a dataset consisting of images and textual content associated with them. Using the topic modeling framework to discover a set of latent topics in such a dataset allows us to re-rank a xed dictionary in a way that prioritizes the words that are more likely to appear in a given image. Moreover, we train a CNN that is able to reproduce those word rankings but using only the image raw pixels as input. We demonstrate that the quality of the automatically obtained custom lexicons is superior to a generic frequency-based baseline. |
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Address | Amsterdam; The Netherlands; October 2016 | ||||
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Area | Expedition | Conference | ECCVW | ||
Notes | DAG; 600.084 | Approved | no | ||
Call Number | Admin @ si @ PGR2016 | Serial | 2825 | ||
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Author | Dan Norton; Fernando Vilariño; Onur Ferhat | ||||
Title | Memory Field – Creative Engagement in Digital Collections | Type | Conference Article | ||
Year | 2015 | Publication | Internet Librarian International Conference | Abbreviated Journal | |
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Abstract | “Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields). | ||||
Address | London; UK; October 2015 | ||||
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Area | Expedition | Conference | ILI | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | Admin @ si @NVF2015 | Serial | 2796 | ||
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Author | Fernando Vilariño; Dimosthenis Karatzas | ||||
Title | The Library Living Lab | Type | Conference Article | ||
Year | 2015 | Publication | Open Living Lab Days | Abbreviated Journal | |
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Address | Istanbul; Turkey; August 2015 | ||||
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Area | Expedition | Conference | OLLD | ||
Notes | MV; DAG;SIAI | Approved | no | ||
Call Number | Admin @ si @ViK2015 | Serial | 2797 | ||
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Author | Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel | ||||
Title | An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres | Type | Book Chapter | ||
Year | 2015 | Publication | The White Book on Public Library Network from Diputació de Barcelona | Abbreviated Journal | |
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Notes | MV; DAG;SIAI | Approved | no | ||
Call Number | Admin @ si @VKC2015 | Serial | 2798 | ||
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