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Author (up) Adriana Romero; Carlo Gatta; Gustavo Camps-Valls
Title Unsupervised Deep Feature Extraction for Remote Sensing Image Classification Type Journal Article
Year 2016 Publication IEEE Transaction on Geoscience and Remote Sensing Abbreviated Journal TGRS
Volume 54 Issue 3 Pages 1349 - 1362
Keywords
Abstract This paper introduces the use of single-layer and deep convolutional networks for remote sensing data analysis. Direct application to multi- and hyperspectral imagery of supervised (shallow or deep) convolutional networks is very challenging given the high input data dimensionality and the relatively small amount of available labeled data. Therefore, we propose the use of greedy layerwise unsupervised pretraining coupled with a highly efficient algorithm for unsupervised learning of sparse features. The algorithm is rooted on sparse representations and enforces both population and lifetime sparsity of the extracted features, simultaneously. We successfully illustrate the expressive power of the extracted representations in several scenarios: classification of aerial scenes, as well as land-use classification in very high resolution or land-cover classification from multi- and hyperspectral images. The proposed algorithm clearly outperforms standard principal component analysis (PCA) and its kernel counterpart (kPCA), as well as current state-of-the-art algorithms of aerial classification, while being extremely computationally efficient at learning representations of data. Results show that single-layer convolutional networks can extract powerful discriminative features only when the receptive field accounts for neighboring pixels and are preferred when the classification requires high resolution and detailed results. However, deep architectures significantly outperform single-layer variants, capturing increasing levels of abstraction and complexity throughout the feature hierarchy.
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 0196-2892 ISBN Medium
Area Expedition Conference
Notes LAMP; 600.079;MILAB Approved no
Call Number Admin @ si @ RGC2016 Serial 2723
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Author (up) Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero
Title Banknote counterfeit detection through background texture printing analysis Type Conference Article
Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper is focused on the detection of counterfeit photocopy banknotes. The main difficulty is to work on a real industrial scenario without any constraint about the acquisition device and with a single image. The main contributions of this paper are twofold: first the adaptation and performance evaluation of existing approaches to classify the genuine and photocopy banknotes using background texture printing analysis, which have not been applied into this context before. Second, a new dataset of Euro banknotes images acquired with several cameras under different luminance conditions to evaluate these methods. Experiments on the proposed algorithms show that mixing SIFT features and sparse coding dictionaries achieves quasi perfect classification using a linear SVM with the created dataset. Approaches using dictionaries to cover all possible texture variations have demonstrated to be robust and outperform the state-of-the-art methods using the proposed benchmark.
Address Rumania; May 2016
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 DAS
Notes DAG; 600.061; 601.269; 600.097 Approved no
Call Number Admin @ si @ BRL2016 Serial 2950
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Author (up) Alejandro Gonzalez Alzate; Zhijie Fang; Yainuvis Socarras; Joan Serrat; David Vazquez; Jiaolong Xu; Antonio Lopez
Title Pedestrian Detection at Day/Night Time with Visible and FIR Cameras: A Comparison Type Journal Article
Year 2016 Publication Sensors Abbreviated Journal SENS
Volume 16 Issue 6 Pages 820
Keywords Pedestrian Detection; FIR
Abstract Despite all the significant advances in pedestrian detection brought by computer vision for driving assistance, it is still a challenging problem. One reason is the extremely varying lighting conditions under which such a detector should operate, namely day and night time. Recent research has shown that the combination of visible and non-visible imaging modalities may increase detection accuracy, where the infrared spectrum plays a critical role. The goal of this paper is to assess the accuracy gain of different pedestrian models (holistic, part-based, patch-based) when training with images in the far infrared spectrum. Specifically, we want to compare detection accuracy on test images recorded at day and nighttime if trained (and tested) using (a) plain color images, (b) just infrared images and (c) both of them. In order to obtain results for the last item we propose an early fusion approach to combine features from both modalities. We base the evaluation on a new dataset we have built for this purpose as well as on the publicly available KAIST multispectral dataset.
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 1424-8220 ISBN Medium
Area Expedition Conference
Notes ADAS; 600.085; 600.076; 600.082; 601.281 Approved no
Call Number ADAS @ adas @ GFS2016 Serial 2754
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Author (up) Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol
Title La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals Type Journal
Year 2016 Publication Lligall, Revista Catalana d'Arxivística Abbreviated Journal
Volume 39 Issue Pages 20-46
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 DAG; 600.097 Approved no
Call Number Admin @ si @ FLR2016 Serial 2897
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Author (up) Alvaro Peris; Marc Bolaños; Petia Radeva; Francisco Casacuberta
Title Video Description Using Bidirectional Recurrent Neural Networks Type Conference Article
Year 2016 Publication 25th International Conference on Artificial Neural Networks Abbreviated Journal
Volume 2 Issue Pages 3-11
Keywords Video description; Neural Machine Translation; Birectional Recurrent Neural Networks; LSTM; Convolutional Neural Networks
Abstract Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions. The combination of Convolutional and Recurrent Neural Networks in these models has proven to outperform the previous state of the art, obtaining more accurate video descriptions. In this work we propose pushing further this model by introducing two contributions into the encoding stage. First, producing richer image representations by combining object and location information from Convolutional Neural Networks and second, introducing Bidirectional Recurrent Neural Networks for capturing both forward and backward temporal relationships in the input frames.
Address Barcelona; September 2016
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 ICANN
Notes MILAB; Approved no
Call Number Admin @ si @ PBR2016 Serial 2833
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Author (up) Anastasios Doulamis; Nikolaos Doulamis; Marco Bertini; Jordi Gonzalez; Thomas B. Moeslund
Title Introduction to the Special Issue on the Analysis and Retrieval of Events/Actions and Workflows in Video Streams Type Journal Article
Year 2016 Publication Multimedia Tools and Applications Abbreviated Journal MTAP
Volume 75 Issue 22 Pages 14985-14990
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 ISE; HUPBA Approved no
Call Number Admin @ si @ DDB2016 Serial 2934
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Author (up) Anders Hast; Alicia Fornes
Title A Segmentation-free Handwritten Word Spotting Approach by Relaxed Feature Matching Type Conference Article
Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 150-155
Keywords
Abstract The automatic recognition of historical handwritten documents is still considered challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results.
Address Santorini; Greece; April 2016
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 DAS
Notes DAG; 602.006; 600.061; 600.077; 600.097 Approved no
Call Number HaF2016 Serial 2753
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Author (up) Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo
Title Monocular visual odometry: A cross-spectral image fusion based approach Type Journal Article
Year 2016 Publication Robotics and Autonomous Systems Abbreviated Journal RAS
Volume 85 Issue Pages 26-36
Keywords Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion
Abstract This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme.
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 ADAS;600.086; 600.076 Approved no
Call Number Admin @ si @SAC2016 Serial 2811
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Author (up) Angel Sappa; P. Carvajal; Cristhian A. Aguilera-Carrasco; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla
Title Wavelet based visible and infrared image fusion: a comparative study Type Journal Article
Year 2016 Publication Sensors Abbreviated Journal SENS
Volume 16 Issue 6 Pages 1-15
Keywords Image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform
Abstract This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR).
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 ADAS; 600.086; 600.076 Approved no
Call Number Admin @ si @SCA2016 Serial 2807
Permanent link to this record
 
 
Author (up) Anjan Dutta; Umapada Pal; Josep Llados
Title Compact Correlated Features for Writer Independent Signature Verification Type Conference Article
Year 2016 Publication 23rd International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper considers the offline signature verification problem which is considered to be an important research line in the field of pattern recognition. In this work we propose hybrid features that consider the local features and their global statistics in the signature image. This has been done by creating a vocabulary of histogram of oriented gradients (HOGs). We impose weights on these local features based on the height information of water reservoirs obtained from the signature. Spatial information between local features are thought to play a vital role in considering the geometry of the signatures which distinguishes the originals from the forged ones. Nevertheless, learning a condensed set of higher order neighbouring features based on visual words, e.g., doublets and triplets, continues to be a challenging problem as possible combinations of visual words grow exponentially. To avoid this explosion of size, we create a code of local pairwise features which are represented as joint descriptors. Local features are paired based on the edges of a graph representation built upon the Delaunay triangulation. We reveal the advantage of combining both type of visual codebooks (order one and pairwise) for signature verification task. This is validated through an encouraging result on two benchmark datasets viz. CEDAR and GPDS300.
Address Cancun; Mexico; December 2016
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 ICPR
Notes DAG; 600.097 Approved no
Call Number Admin @ si @ DPL2016 Serial 2875
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Author (up) Antoni Gurgui; Debora Gil; Enric Marti; Vicente Grau
Title Left-Ventricle Basal Region Constrained Parametric Mapping to Unitary Domain Type Conference Article
Year 2016 Publication 7th International Workshop on Statistical Atlases & Computational Modelling of the Heart Abbreviated Journal
Volume 10124 Issue Pages 163-171
Keywords Laplacian; Constrained maps; Parameterization; Basal ring
Abstract Due to its complex geometry, the basal ring is often omitted when putting different heart geometries into correspondence. In this paper, we present the first results on a new mapping of the left ventricle basal rings onto a normalized coordinate system using a fold-over free approach to the solution to the Laplacian. To guarantee correspondences between different basal rings, we imposed some internal constrained positions at anatomical landmarks in the normalized coordinate system. To prevent internal fold-overs, constraints are handled by cutting the volume into regions defined by anatomical features and mapping each piece of the volume separately. Initial results presented in this paper indicate that our method is able to handle internal constrains without introducing fold-overs and thus guarantees one-to-one mappings between different basal ring geometries.
Address Athens; 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 STACOM
Notes IAM; Approved no
Call Number Admin @ si @ GGM2016 Serial 2884
Permanent link to this record
 
 
Author (up) Antonio Esteban Lansaque; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil
Title Stable Anatomical Structure Tracking for video-bronchoscopy Navigation Type Conference Article
Year 2016 Publication 19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops Abbreviated Journal
Volume Issue Pages
Keywords Lung cancer diagnosis; video-bronchoscopy; airway lumen detection; region tracking
Abstract Bronchoscopy allows to examine the patient airways for detection of lesions and sampling of tissues without surgery. A main drawback in lung cancer diagnosis is the diculty to check whether the exploration is following the correct path to the nodule that has to be biopsied. The most extended guidance uses uoroscopy which implies repeated radiation of clinical sta and patients. Alternatives such as virtual bronchoscopy or electromagnetic navigation are very expensive and not completely robust to blood, mocus or deformations as to be extensively used. We propose a method that extracts and tracks stable lumen regions at di erent levels of the bronchial tree. The tracked regions are stored in a tree that encodes the anatomical structure of the scene which can be useful to retrieve the path to the lesion that the clinician should follow to do the biopsy. We present a multi-expert validation of our anatomical landmark extraction in 3 intra-operative ultrathin explorations.
Address Athens; Greece; October 2016
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 MICCAIW
Notes IAM; 600.075 Approved no
Call Number Admin @ si @ LSB2016b Serial 2857
Permanent link to this record
 
 
Author (up) Antonio Esteban Lansaque; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil
Title Stable Airway Center Tracking for Bronchoscopic Navigation Type Conference Article
Year 2016 Publication 28th Conference of the international Society for Medical Innovation and Technology Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Bronchoscopists use X‐ray fluoroscopy to guide bronchoscopes to the lesion to be biopsied without any kind of incisions. Reducing exposure to X‐ray is important for both patients and doctors but alternatives like electromagnetic navigation require specific equipment and increase the cost of the clinical procedure. We propose a guiding system based on the extraction of airway centers from intra‐operative videos. Such anatomical landmarks could be
matched to the airway centerline extracted from a pre‐planned CT to indicate the best path to the lesion. We present an extraction of lumen centers
from intra‐operative videos based on tracking of maximal stable regions of energy maps.
Address Delft; Rotterdam; Leiden; The Netherlands; October 2016
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 SMIT
Notes IAM; Approved no
Call Number Admin @ si @ LSB2016a Serial 2856
Permanent link to this record
 
 
Author (up) Antonio Hernandez; Sergio Escalera; Stan Sclaroff
Title Poselet-basedContextual Rescoring for Human Pose Estimation via Pictorial Structures Type Journal Article
Year 2016 Publication International Journal of Computer Vision Abbreviated Journal IJCV
Volume 118 Issue 1 Pages 49–64
Keywords Contextual rescoring; Poselets; Human pose estimation
Abstract In this paper we propose a contextual rescoring method for predicting the position of body parts in a human pose estimation framework. A set of poselets is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body part hypotheses. A method is proposed for the automatic discovery of a compact subset of poselets that covers the different poses in a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for each body joint detection, given its relationship to detections of other body joints and mid-level parts in the image. This new score is incorporated in the pictorial structure model as an additional unary potential, following the recent work of Pishchulin et al. Experiments on two benchmarks show comparable results to Pishchulin et al. while reducing the size of the mid-level representation by an order of magnitude, reducing the execution time by 68 % accordingly.
Address
Corporate Author Thesis
Publisher Springer US Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0920-5691 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB; Approved no
Call Number Admin @ si @ HES2016 Serial 2719
Permanent link to this record
 
 
Author (up) Arash Akbarinia; C. Alejandro Parraga
Title Biologically plausible boundary detection Type Conference Article
Year 2016 Publication 27th British Machine Vision Conference Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Edges are key components of any visual scene to the extent that we can recognise objects merely by their silhouettes. The human visual system captures edge information through neurons in the visual cortex that are sensitive to both intensity discontinuities and particular orientations. The “classical approach” assumes that these cells are only responsive to the stimulus present within their receptive fields, however, recent studies demonstrate that surrounding regions and inter-areal feedback connections influence their responses significantly. In this work we propose a biologically-inspired edge detection model in which orientation selective neurons are represented through the first derivative of a Gaussian function resembling double-opponent cells in the primary visual cortex (V1). In our model we account for four kinds of surround, i.e. full, far, iso- and orthogonal-orientation, whose contributions are contrast-dependant. The output signal from V1 is pooled in its perpendicular direction by larger V2 neurons employing a contrast-variant centre-surround kernel. We further introduce a feedback connection from higher-level visual areas to the lower ones. The results of our model on two benchmark datasets show a big improvement compared to the current non-learning and biologically-inspired state-of-the-art algorithms while being competitive to the learning-based methods.
Address York; UK; September 2016
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 BMVC
Notes NEUROBIT; 600.068; 600.072 Approved no
Call Number Admin @ si @ AkP2016a Serial 2867
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