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Author Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus edit   pdf
openurl 
  Title Color Naming Type Book Chapter
  Year 2012 Publication Color in Computer Vision: Fundamentals and Applications Abbreviated Journal  
  Volume Issue (up) 17 Pages 287-317  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher John Wiley & Sons, Ltd. Place of Publication Editor Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ WBV2012 Serial 2063  
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Author J.S. Cope; P.Remagnino; S.Mannan; Katerine Diaz; Francesc J. Ferri; P.Wilkin edit  url
doi  openurl
  Title Reverse Engineering Expert Visual Observations: From Fixations To The Learning Of Spatial Filters With A Neural-Gas Algorithm Type Journal Article
  Year 2013 Publication Expert Systems with Applications Abbreviated Journal EXWA  
  Volume 40 Issue (up) 17 Pages 6707-6712  
  Keywords Neural gas; Expert vision; Eye-tracking; Fixations  
  Abstract Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give high responses to image regions which a human expert fixated on. These filters can then be used to identify regions in other images which are likely to be useful for a given vision task. The algorithm is evaluated by learning filters for locating specific areas of plant leaves.  
  Address  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0957-4174 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ CRM2013 Serial 2438  
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Author Josep Llados; Dimosthenis Karatzas; Joan Mas; Gemma Sanchez edit  openurl
  Title A Generic Architecture for the Conversion of Document Collections into Semantically Annotated Digital Archives Type Journal
  Year 2008 Publication Journal of Universal Computer Science Abbreviated Journal  
  Volume 14 Issue (up) 18 Pages 2912–2935  
  Keywords Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition  
  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 Approved no  
  Call Number DAG @ dag @ LKM2008 Serial 1142  
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Author Andres Traumann; Gholamreza Anbarjafari; Sergio Escalera edit  doi
openurl 
  Title Accurate 3D Measurement Using Optical Depth Information Type Journal Article
  Year 2015 Publication Electronic Letters Abbreviated Journal EL  
  Volume 51 Issue (up) 18 Pages 1420-1422  
  Keywords  
  Abstract A novel three-dimensional measurement technique is proposed. The methodology consists in mapping from the screen coordinates reported by the optical camera to the real world, and integrating distance gradients from the beginning to the end point, while also minimising the error through fitting pixel locations to a smooth curve. The results demonstrate accuracy of less than half a centimetre using Microsoft Kinect II.  
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  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 HuPBA;MILAB Approved no  
  Call Number Admin @ si @ TAE2015 Serial 2647  
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Author Egils Avots; Meysam Madadi; Sergio Escalera; Jordi Gonzalez; Xavier Baro; Paul Pallin; Gholamreza Anbarjafari edit   pdf
url  doi
openurl 
  Title From 2D to 3D geodesic-based garment matching Type Journal Article
  Year 2019 Publication Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 78 Issue (up) 18 Pages 25829–25853  
  Keywords Shape matching; Geodesic distance; Texture mapping; RGBD image processing; Gaussian mixture model  
  Abstract A new approach for 2D to 3D garment retexturing is proposed based on Gaussian mixture models and thin plate splines (TPS). An automatically segmented garment of an individual is matched to a new source garment and rendered, resulting in augmented images in which the target garment has been retextured using the texture of the source garment. We divide the problem into garment boundary matching based on Gaussian mixture models and then interpolate inner points using surface topology extracted through geodesic paths, which leads to a more realistic result than standard approaches. We evaluated and compared our system quantitatively by root mean square error (RMS) and qualitatively using the mean opinion score (MOS), showing the benefits of the proposed methodology on our gathered 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 ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA; ISE; 600.098; 600.119; 602.133 Approved no  
  Call Number Admin @ si @ AME2019 Serial 3317  
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Author Andre Litvin; Kamal Nasrollahi; Sergio Escalera; Cagri Ozcinar; Thomas B. Moeslund; Gholamreza Anbarjafari edit  url
openurl 
  Title A Novel Deep Network Architecture for Reconstructing RGB Facial Images from Thermal for Face Recognition Type Journal Article
  Year 2019 Publication Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 78 Issue (up) 18 Pages 25259–25271  
  Keywords Fully convolutional networks; FusionNet; Thermal imaging; Face recognition  
  Abstract This work proposes a fully convolutional network architecture for RGB face image generation from a given input thermal face image to be applied in face recognition scenarios. The proposed method is based on the FusionNet architecture and increases robustness against overfitting using dropout after bridge connections, randomised leaky ReLUs (RReLUs), and orthogonal regularization. Furthermore, we propose to use a decoding block with resize convolution instead of transposed convolution to improve final RGB face image generation. To validate our proposed network architecture, we train a face classifier and compare its face recognition rate on the reconstructed RGB images from the proposed architecture, to those when reconstructing images with the original FusionNet, as well as when using the original RGB images. As a result, we are introducing a new architecture which leads to a more accurate network.  
  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 HuPBA; no menciona Approved no  
  Call Number Admin @ si @ LNE2019 Serial 3318  
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Author Wenwen Fu; Zhihong An; Wendong Huang; Haoran Sun; Wenjuan Gong; Jordi Gonzalez edit  url
openurl 
  Title A Spatio-Temporal Spotting Network with Sliding Windows for Micro-Expression Detection Type Journal Article
  Year 2023 Publication Electronics Abbreviated Journal ELEC  
  Volume 12 Issue (up) 18 Pages 3947  
  Keywords micro-expression spotting; sliding window; key frame extraction  
  Abstract Micro-expressions reveal underlying emotions and are widely applied in political psychology, lie detection, law enforcement and medical care. Micro-expression spotting aims to detect the temporal locations of facial expressions from video sequences and is a crucial task in micro-expression recognition. In this study, the problem of micro-expression spotting is formulated as micro-expression classification per frame. We propose an effective spotting model with sliding windows called the spatio-temporal spotting network. The method involves a sliding window detection mechanism, combines the spatial features from the local key frames and the global temporal features and performs micro-expression spotting. The experiments are conducted on the CAS(ME)2 database and the SAMM Long Videos database, and the results demonstrate that the proposed method outperforms the state-of-the-art method by 30.58% for the CAS(ME)2 and 23.98% for the SAMM Long Videos according to overall F-scores.  
  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 Approved no  
  Call Number Admin @ si @ FAH2023 Serial 3864  
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Author Anders Skaarup Johansen; Kamal Nasrollahi; Sergio Escalera; Thomas B. Moeslund edit  url
doi  openurl
  Title Who Cares about the Weather? Inferring Weather Conditions for Weather-Aware Object Detection in Thermal Images Type Journal Article
  Year 2023 Publication Applied Sciences Abbreviated Journal AS  
  Volume 13 Issue (up) 18 Pages  
  Keywords thermal; object detection; concept drift; conditioning; weather recognition  
  Abstract Deployments of real-world object detection systems often experience a degradation in performance over time due to concept drift. Systems that leverage thermal cameras are especially susceptible because the respective thermal signatures of objects and their surroundings are highly sensitive to environmental changes. In this study, two types of weather-aware latent conditioning methods are investigated. The proposed method aims to guide two object detectors, (YOLOv5 and Deformable DETR) to become weather-aware. This is achieved by leveraging an auxiliary branch that predicts weather-related information while conditioning intermediate layers of the object detector. While the conditioning methods proposed do not directly improve the accuracy of baseline detectors, it can be observed that conditioned networks manage to extract a weather-related signal from the thermal images, thus resulting in a decreased miss rate at the cost of increased false positives. The extracted signal appears noisy and is thus challenging to regress accurately. This is most likely a result of the qualitative nature of the thermal sensor; thus, further work is needed to identify an ideal method for optimizing the conditioning branch, as well as to further improve the accuracy of the system.  
  Address  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HUPBA Approved no  
  Call Number Admin @ si @ SNE2023 Serial 3983  
Permanent link to this record
 

 
Author Javier Marin; Sergio Escalera edit   pdf
url  openurl
  Title SSSGAN: Satellite Style and Structure Generative Adversarial Networks Type Journal Article
  Year 2021 Publication Remote Sensing Abbreviated Journal  
  Volume 13 Issue (up) 19 Pages 3984  
  Keywords  
  Abstract This work presents Satellite Style and Structure Generative Adversarial Network (SSGAN), a generative model of high resolution satellite imagery to support image segmentation. Based on spatially adaptive denormalization modules (SPADE) that modulate the activations with respect to segmentation map structure, in addition to global descriptor vectors that capture the semantic information in a vector with respect to Open Street Maps (OSM) classes, this model is able to produce
consistent aerial imagery. By decoupling the generation of aerial images into a structure map and a carefully defined style vector, we were able to improve the realism and geodiversity of the synthesis with respect to the state-of-the-art baseline. Therefore, the proposed model allows us to control the generation not only with respect to the desired structure, but also with respect to a geographic area.
 
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  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes HUPBA; no proj Approved no  
  Call Number Admin @ si @ MaE2021 Serial 3651  
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 (up) 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 DAG; IAM Approved no  
  Call Number IAM @ iam @ SLE1998 Serial 1573  
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Author Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso edit  url
openurl 
  Title Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation Type Journal Article
  Year 2017 Publication Journal of Thoracic Oncology Abbreviated Journal JTO  
  Volume 12 Issue (up) 1S Pages S596-S597  
  Keywords Thorax CT; diagnosis; Peripheral Pulmonary Nodule  
  Abstract A main weakness of virtual bronchoscopic navigation (VBN) is unsuccessful segmentation of distal branches approaching peripheral pulmonary nodules (PPN). CT scan acquisition protocol is pivotal for segmentation covering the utmost periphery. We hypothesize that application of continuous positive airway pressure (CPAP) during CT acquisition could improve visualization and segmentation of peripheral bronchi. The purpose of the present pilot study is to compare quality of segmentations under 4 CT acquisition modes: inspiration (INSP), expiration (EXP) and both with CPAP (INSP-CPAP and EXP-CPAP).  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ DGC2017a Serial 2883  
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Author Amir A.Amini; Yasheng Chen; Mohamed Elayyadi; Petia Radeva edit   pdf
openurl 
  Title Tag Surface Reconstruction and Tracking of Myocardial Beads from SPAMM-MRI with Parametric B-Spline Surfaces Type Journal
  Year 2001 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI  
  Volume 20 Issue (up) 2 Pages 94–103  
  Keywords B-spline surfaces, cardiac motion, myocardial beads, myocardial infarction, tagged MRI.  
  Abstract Magnetic resonance imaging (MRI) is unique in its ability to noninvasively and selectively alter tissue magnetization, and create tag planes intersecting image slices. The resulting grid of signal voids allows for tracking deformations of tissues in otherwise homogeneous-signal myocardial regions. In this paper, we propose a specific spatial modulation of magnetization (SPAMM) imaging protocol together with efficient techniques for measurement of three-dimensional (3-D) motion of material points of the human heart (referred to as myocardial beads) from images collected with the SPAMM method. The techniques make use of tagged images in orthogonal views by explicitly reconstructing 3-D B-spline surface representation of tag planes (tag planes in two orthogonal orientations intersecting the short-axis (SA) image slices and tag planes in an orientation orthogonal to the short-axis tag planes intersecting long-axis (LA) image slices). The developed methods allow for viewing deformations of 3-D tag surfaces, spatial correspondence of long-axis and short-axis image slice and tag positions, as well as nonrigid movement of myocardial beads as a function of time.  
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  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ ACE2001; IAM @ iam @ ACE2001 Serial 180  
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Author Judit Martinez edit  openurl
  Title Automotive sector and Machine Vision Type Miscellaneous
  Year 2002 Publication European Integrated Machine Vision, Special Edition: Automative and Glass Abbreviated Journal  
  Volume 1 Issue (up) 2 Pages  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ 37316 Serial 270  
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Author Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva edit  openurl
  Title Utilizacion de la estructura de los campos vectoriales para la deteccion de la Adventicia en imagenes de Ecografia Intracoronaria Type Journal
  Year 2004 Publication Revista Española de Cardiología Abbreviated Journal REC  
  Volume 57 Issue (up) 2 Pages 100  
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  ISSN ISBN Medium  
  Area Expedition Conference SEC  
  Notes MILAB;IAM Approved no  
  Call Number BCNPCL @ bcnpcl @ RMF2004 Serial 566  
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Author Joaquin Salas; Wendy Avalos; Rafael Castañeda; Mario Maya edit  openurl
  Title A machine-vision system to measure the parameters describing the performance of a Foucault pendulum Type Journal
  Year 2006 Publication Machine Vision and Applications Abbreviated Journal  
  Volume 17 Issue (up) 2 Pages 133–138  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ SAC2006 Serial 644  
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