Home << 1 2 3 4 5 6 7 8 9 10 >> [11–11]
List View
 | 
Citations
 | 
Details
   web
Records
Author (up) Adria Rico; Alicia Fornes
Title Camera-based Optical Music Recognition using a Convolutional Neural Network Type Conference Article
Year 2017 Publication 12th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages 27-28
Keywords optical music recognition; document analysis; convolutional neural network; deep learning
Abstract Optical Music Recognition (OMR) consists in recognizing images of music scores. Contrary to expectation, the current OMR systems usually fail when recognizing images of scores captured by digital cameras and smartphones. In this work, we propose a camera-based OMR system based on Convolutional Neural Networks, showing promising preliminary results
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 GREC
Notes DAG;600.097; 600.121 Approved no
Call Number Admin @ si @ RiF2017 Serial 3059
Permanent link to this record
 
 
Author (up) Aitor Alvarez-Gila; Joost Van de Weijer; Estibaliz Garrote
Title Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB Type Conference Article
Year 2017 Publication 1st International Workshop on Physics Based Vision meets Deep Learning Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Hyperspectral signal reconstruction aims at recovering the original spectral input that produced a certain trichromatic (RGB) response from a capturing device or observer.
Given the heavily underconstrained, non-linear nature of the problem, traditional techniques leverage different statistical properties of the spectral signal in order to build informative priors from real world object reflectances for constructing such RGB to spectral signal mapping. However,
most of them treat each sample independently, and thus do not benefit from the contextual information that the spatial dimensions can provide. We pose hyperspectral natural image reconstruction as an image to image mapping learning problem, and apply a conditional generative adversarial framework to help capture spatial semantics. This is the first time Convolutional Neural Networks -and, particularly, Generative Adversarial Networks- are used to solve this task. Quantitative evaluation shows a Root Mean Squared Error (RMSE) drop of 44:7% and a Relative RMSE drop of 47:0% on the ICVL natural hyperspectral image dataset.
Address Venice; Italy; October 2017
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 ICCV-PBDL
Notes LAMP; 600.109; 600.106; 600.120 Approved no
Call Number Admin @ si @ AWG2017 Serial 2969
Permanent link to this record
 
 
Author (up) Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero
Title e-Counterfeit: a mobile-server platform for document counterfeit detection Type Conference Article
Year 2017 Publication 14th IAPR International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms.
Address Kyoto; Japan; November 2017
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 ICDAR
Notes DAG; 600.061; 600.097; 600.121 Approved no
Call Number Admin @ si @ BRL2018 Serial 3084
Permanent link to this record
 
 
Author (up) Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero
Title Evaluation of Texture Descriptors for Validation of Counterfeit Documents Type Conference Article
Year 2017 Publication 14th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1237-1242
Keywords
Abstract This paper describes an exhaustive comparative analysis and evaluation of different existing texture descriptor algorithms to differentiate between genuine and counterfeit documents. We include in our experiments different categories of algorithms and compare them in different scenarios with several counterfeit datasets, comprising banknotes and identity documents. Computational time in the extraction of each descriptor is important because the final objective is to use it in a real industrial scenario. HoG and CNN based descriptors stands out statistically over the rest in terms of the F1-score/time ratio 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 2379-2140 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG; 600.061; 601.269; 600.097; 600.121 Approved no
Call Number Admin @ si @ BRL2017 Serial 3092
Permanent link to this record
 
 
Author (up) Albert Clapes; Tinne Tuytelaars; Sergio Escalera
Title Darwintrees for action recognition Type Conference Article
Year 2017 Publication Chalearn Workshop on Action, Gesture, and Emotion Recognition: Large Scale Multimodal Gesture Recognition and Real versus Fake expressed emotions at ICCV 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 ICCVW
Notes HUPBA; no menciona Approved no
Call Number Admin @ si @ CTE2017 Serial 3069
Permanent link to this record
 
 
Author (up) Alejandro Cartas; Mariella Dimiccoli; Petia Radeva
Title Batch-based activity recognition from egocentric photo-streams Type Conference Article
Year 2017 Publication 1st International workshop on Egocentric Perception, Interaction and Computing Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Activity recognition from long unstructured egocentric photo-streams has several applications in assistive technology such as health monitoring and frailty detection, just to name a few. However, one of its main technical challenges is to deal with the low frame rate of wearable photo-cameras, which causes abrupt appearance changes between consecutive frames. In consequence, important discriminatory low-level features from motion such as optical flow cannot be estimated. In this paper, we present a batch-driven approach for training a deep learning architecture that strongly rely on Long short-term units to tackle this problem. We propose two different implementations of the same approach that process a photo-stream sequence using batches of fixed size with the goal of capturing the temporal evolution of high-level features. The main difference between these implementations is that one explicitly models consecutive batches by overlapping them. Experimental results over a public dataset acquired by three users demonstrate the validity of the proposed architectures to exploit the temporal evolution of convolutional features over time without relying on event boundaries.
Address Venice; Italy; October 2017;
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 ICCV - EPIC
Notes MILAB; no menciona Approved no
Call Number Admin @ si @ CDR2017 Serial 3023
Permanent link to this record
 
 
Author (up) Alejandro Gonzalez Alzate; David Vazquez; Antonio Lopez; Jaume Amores
Title On-Board Object Detection: Multicue, Multimodal, and Multiview Random Forest of Local Experts Type Journal Article
Year 2017 Publication IEEE Transactions on cybernetics Abbreviated Journal Cyber
Volume 47 Issue 11 Pages 3980 - 3990
Keywords Multicue; multimodal; multiview; object detection
Abstract Despite recent significant advances, object detection continues to be an extremely challenging problem in real scenarios. In order to develop a detector that successfully operates under these conditions, it becomes critical to leverage upon multiple cues, multiple imaging modalities, and a strong multiview (MV) classifier that accounts for different object views and poses. In this paper, we provide an extensive evaluation that gives insight into how each of these aspects (multicue, multimodality, and strong MV classifier) affect accuracy both individually and when integrated together. In the multimodality component, we explore the fusion of RGB and depth maps obtained by high-definition light detection and ranging, a type of modality that is starting to receive increasing attention. As our analysis reveals, although all the aforementioned aspects significantly help in improving the accuracy, the fusion of visible spectrum and depth information allows to boost the accuracy by a much larger margin. The resulting detector not only ranks among the top best performers in the challenging KITTI benchmark, but it is built upon very simple blocks that are easy to implement and computationally efficient.
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 2168-2267 ISBN Medium
Area Expedition Conference
Notes ADAS; 600.085; 600.082; 600.076; 600.118 Approved no
Call Number Admin @ si @ Serial 2810
Permanent link to this record
 
 
Author (up) Alexey Dosovitskiy; German Ros; Felipe Codevilla; Antonio Lopez; Vladlen Koltun
Title CARLA: An Open Urban Driving Simulator Type Conference Article
Year 2017 Publication 1st Annual Conference on Robot Learning. Proceedings of Machine Learning Abbreviated Journal
Volume 78 Issue Pages 1-16
Keywords Autonomous driving; sensorimotor control; simulation
Abstract We introduce CARLA, an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous urban driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites and environmental conditions. We use CARLA to study the performance of three approaches to autonomous driving: a classic modular pipeline, an endto-end
model trained via imitation learning, and an end-to-end model trained via
reinforcement learning. The approaches are evaluated in controlled scenarios of
increasing difficulty, and their performance is examined via metrics provided by CARLA, illustrating the platform’s utility for autonomous driving research.
Address Mountain View; CA; USA; November 2017
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 CORL
Notes ADAS; 600.085; 600.118 Approved no
Call Number Admin @ si @ DRC2017 Serial 2988
Permanent link to this record
 
 
Author (up) Alicia Fornes; Beata Megyesi; Joan Mas
Title Transcription of Encoded Manuscripts with Image Processing Techniques Type Conference Article
Year 2017 Publication Digital Humanities Conference Abbreviated Journal
Volume Issue Pages 441-443
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 DH
Notes DAG; 600.097; 600.121 Approved no
Call Number Admin @ si @ FMM2017 Serial 3061
Permanent link to this record
 
 
Author (up) Alicia Fornes; Veronica Romero; Arnau Baro; Juan Ignacio Toledo; Joan Andreu Sanchez; Enrique Vidal; Josep Llados
Title ICDAR2017 Competition on Information Extraction in Historical Handwritten Records Type Conference Article
Year 2017 Publication 14th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1389-1394
Keywords
Abstract The extraction of relevant information from historical handwritten document collections is one of the key steps in order to make these manuscripts available for access and searches. In this competition, the goal is to detect the named entities and assign each of them a semantic category, and therefore, to simulate the filling in of a knowledge database. This paper describes the dataset, the tasks, the evaluation metrics, the participants methods and the results.
Address Kyoto; Japan; November 2017
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 ICDAR
Notes DAG; 600.097; 601.225; 600.121 Approved no
Call Number Admin @ si @ FRB2017 Serial 3052
Permanent link to this record
 
 
Author (up) Andrei Polzounov; Artsiom Ablavatski; Sergio Escalera; Shijian Lu; Jianfei Cai
Title WordFences: Text Localization and Recognition Type Conference Article
Year 2017 Publication 24th International Conference on Image Processing Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Beijing; China; September 2017
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 ICIP
Notes HUPBA; no menciona Approved no
Call Number Admin @ si @ PAE2017 Serial 3007
Permanent link to this record
 
 
Author (up) Angel Valencia; Roger Idrovo; Angel Sappa; Douglas Plaza; Daniel Ochoa
Title A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers Type Conference Article
Year 2017 Publication IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics Abbreviated Journal
Volume Issue Pages
Keywords
Abstract In general, robot grasping approaches are based on the usage of multi-finger grippers. However, when large size objects need to be manipulated vacuum grippers are preferred, instead of finger based grippers. This paper aims to estimate the best picking place for a two suction cups vacuum gripper,
when planar objects with an unknown size and geometry are considered. The approach is based on the estimation of geometric properties of object’s shape from a partial cloud of points (a single 3D view), in such a way that combine with considerations of a theoretical model to generate an optimal contact point
that minimizes the vacuum force needed to guarantee a grasp.
Experimental results in real scenarios are presented to show the validity of the proposed approach.
Address San Sebastian; Spain; May 2017
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 ECMSM
Notes ADAS; 600.086; 600.118 Approved no
Call Number Admin @ si @ VIS2017 Serial 2917
Permanent link to this record
 
 
Author (up) Aniol Lidon; Marc Bolaños; Mariella Dimiccoli; Petia Radeva; Maite Garolera; Xavier Giro
Title Semantic Summarization of Egocentric Photo-Stream Events Type Conference Article
Year 2017 Publication 2nd Workshop on Lifelogging Tools and Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address San Francisco; USA; October 2017
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 978-1-4503-5503-2 Medium
Area Expedition Conference ACMW (LTA)
Notes MILAB; no proj Approved no
Call Number Admin @ si @ LBD2017 Serial 3024
Permanent link to this record
 
 
Author (up) Anjan Dutta; Pau Riba; Josep Llados; Alicia Fornes
Title Pyramidal Stochastic Graphlet Embedding for Document Pattern Classification Type Conference Article
Year 2017 Publication 14th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 33-38
Keywords graph embedding; hierarchical graph representation; graph clustering; stochastic graphlet embedding; graph classification
Abstract Document pattern classification methods using graphs have received a lot of attention because of its robust representation paradigm and rich theoretical background. However, the way of preserving and the process for delineating documents with graphs introduce noise in the rendition of underlying data, which creates instability in the graph representation. To deal with such unreliability in representation, in this paper, we propose Pyramidal Stochastic Graphlet Embedding (PSGE).
Given a graph representing a document pattern, our method first computes a graph pyramid by successively reducing the base graph. Once the graph pyramid is computed, we apply Stochastic Graphlet Embedding (SGE) for each level of the pyramid and combine their embedded representation to obtain a global delineation of the original graph. The consideration of pyramid of graphs rather than just a base graph extends the representational power of the graph embedding, which reduces the instability caused due to noise and distortion. When plugged with support
vector machine, our proposed PSGE has outperformed the state-of-the-art results in recognition of handwritten words as well as graphical symbols
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 ICDAR
Notes DAG; 600.097; 601.302; 600.121 Approved no
Call Number Admin @ si @ DRL2017 Serial 3054
Permanent link to this record
 
 
Author (up) Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez
Title Computer Vision in Vehicle Technology: Land, Sea & Air Type Book Whole
Year 2017 Publication Abbreviated Journal
Volume Issue Pages 161-163
Keywords
Abstract Summary This chapter examines different vision-based commercial solutions for real-live problems related to vehicles. It is worth mentioning the recent astonishing performance of deep convolutional neural networks (DCNNs) in difficult visual tasks such as image classification, object recognition/localization/detection, and semantic segmentation. In fact,
different DCNN architectures are already being explored for low-level tasks such as optical flow and disparity computation, and higher level ones such as place recognition.
Address
Corporate Author Thesis
Publisher John Wiley & Sons, Ltd Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-118-86807-2 Medium
Area Expedition Conference
Notes ADAS; 600.118 Approved no
Call Number Admin @ si @ LIP2017a Serial 2937
Permanent link to this record