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Author (up) Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud edit   pdf
doi  openurl
  Title A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super-Resolution Type Journal Article
  Year 2022 Publication Sensors Abbreviated Journal SENS  
  Volume 22 Issue 6 Pages 2254  
  Keywords Thermal image super-resolution; unsupervised super-resolution; thermal images; attention module; semiregistered thermal images  
  Abstract This paper presents a transfer domain strategy to tackle the limitations of low-resolution thermal sensors and generate higher-resolution images of reasonable quality. The proposed technique employs a CycleGAN architecture and uses a ResNet as an encoder in the generator along with an attention module and a novel loss function. The network is trained on a multi-resolution thermal image dataset acquired with three different thermal sensors. Results report better performance benchmarking results on the 2nd CVPR-PBVS-2021 thermal image super-resolution challenge than state-of-the-art methods. The code of this work is available online.  
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  Corporate Author Thesis  
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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 MSIAU; Approved no  
  Call Number Admin @ si @ RSV2022b Serial 3688  
Permanent link to this record
 

 
Author (up) Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla; Sabari Nathan; Priya Kansal; Armin Mehri; Parichehr Behjati Ardakani; A.Dalal; A.Akula; D.Sharma; S.Pandey; B.Kumar; J.Yao; R.Wu; KFeng; N.Li; Y.Zhao; H.Patel; V. Chudasama; K.Pjajapati; A.Sarvaiya; K.Upla; K.Raja; R.Ramachandra; C.Bush; F.Almasri; T.Vandamme; O.Debeir; N.Gutierrez; Q.Nguyen; W.Beksi edit   pdf
url  doi
openurl 
  Title Thermal Image Super-Resolution Challenge – PBVS 2021 Type Conference Article
  Year 2021 Publication Conference on Computer Vision and Pattern Recognition Workshops Abbreviated Journal  
  Volume Issue Pages 4359-4367  
  Keywords  
  Abstract This paper presents results from the second Thermal Image Super-Resolution (TISR) challenge organized in the framework of the Perception Beyond the Visible Spectrum (PBVS) 2021 workshop. For this second edition, the same thermal image dataset considered during the first challenge has been used; only mid-resolution (MR) and high-resolution (HR) sets have been considered. The dataset consists of 951 training images and 50 testing images for each resolution. A set of 20 images for each resolution is kept aside for evaluation. The two evaluation methodologies proposed for the first challenge are also considered in this opportunity. The first evaluation task consists of measuring the PSNR and SSIM between the obtained SR image and the corresponding ground truth (i.e., the HR thermal image downsampled by four). The second evaluation also consists of measuring the PSNR and SSIM, but in this case, considers the x2 SR obtained from the given MR thermal image; this evaluation is performed between the SR image with respect to the semi-registered HR image, which has been acquired with another camera. The results outperformed those from the first challenge, thus showing an improvement in both evaluation metrics.  
  Address Virtual; June 2021  
  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 CVPRW  
  Notes MSIAU; 600.130; 600.122 Approved no  
  Call Number Admin @ si @ RSV2021 Serial 3581  
Permanent link to this record
 

 
Author (up) Rafael E. Rivadeneira; Henry Velesaca; Angel Sappa edit  url
doi  openurl
  Title Object Detection in Very Low-Resolution Thermal Images through a Guided-Based Super-Resolution Approach Type Conference Article
  Year 2023 Publication 17th International Conference on Signal-Image Technology & Internet-Based Systems Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This work proposes a novel approach that integrates super-resolution techniques with off-the-shelf object detection methods to tackle the problem of handling very low-resolution thermal images. The suggested approach begins by enhancing the low-resolution (LR) thermal images through a guided super-resolution strategy, leveraging a high-resolution (HR) visible spectrum image. Subsequently, object detection is performed on the high-resolution thermal image. The experimental results demonstrate tremendous improvements in comparison with both scenarios: when object detection is performed on the LR thermal image alone, as well as when object detection is conducted on the up-sampled LR thermal image. Moreover, the proposed approach proves highly valuable in camouflaged scenarios where objects might remain undetected in visible spectrum images.  
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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 SITIS  
  Notes MSIAU Approved no  
  Call Number Admin @ si @ RVS2023 Serial 4010  
Permanent link to this record
 

 
Author (up) Rafael E. Rivadeneira; Patricia Suarez; Angel Sappa; Boris X. Vintimilla edit   pdf
url  openurl
  Title Thermal Image SuperResolution Through Deep Convolutional Neural Network Type Conference Article
  Year 2019 Publication 16th International Conference on Images Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 417-426  
  Keywords  
  Abstract Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a super-resolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process, a new thermal images dataset is used. Different experiments have been carried out, firstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www.
cidis.espol.edu.ec/es/dataset.
 
  Address Waterloo; Canada; August 2019  
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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 ICIAR  
  Notes MSIAU; 600.130; 601.349; 600.122 Approved no  
  Call Number Admin @ si @ RSS2019 Serial 3269  
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Author (up) Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet edit   pdf
doi  openurl
  Title Towards multispectral data acquisition with hand-held devices Type Conference Article
  Year 2013 Publication 20th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 2053 - 2057  
  Keywords Multispectral; mobile devices; color measurements  
  Abstract We propose a method to acquire multispectral data with handheld devices with front-mounted RGB cameras. We propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and
blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results are promising and show that the accuracy of the spectral reconstruction improves in the range from 30-40% over the spectral
reconstruction based on a single illuminant. Furthermore, we propose to compute sensor-illuminant aware linear basis by discarding the part of the reflectances that falls in the sensorilluminant null-space. We show experimentally that optimizing reflectance estimation on these new basis functions decreases
the RMSE significantly over basis functions that are independent to sensor-illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops, opening up applications which are currently considered to be unrealistic.
 
  Address Melbourne; Australia; September 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 ICIP  
  Notes CIC; DAG; 600.048 Approved no  
  Call Number Admin @ si @ KWK2013b Serial 2265  
Permanent link to this record
 

 
Author (up) Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat edit   pdf
doi  openurl
  Title Discriminative Color Descriptors Type Conference Article
  Year 2013 Publication IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2866 - 2873  
  Keywords  
  Abstract Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200.  
  Address Portland; Oregon; June 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 1063-6919 ISBN Medium  
  Area Expedition Conference CVPR  
  Notes CIC; 600.048 Approved no  
  Call Number Admin @ si @ KWK2013a Serial 2262  
Permanent link to this record
 

 
Author (up) Rahma Kalboussi; Aymen Azaza; Joost Van de Weijer; Mehrez Abdellaoui; Ali Douik edit  url
openurl 
  Title Object proposals for salient object segmentation in videos Type Journal Article
  Year 2020 Publication Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 79 Issue 13 Pages 8677-8693  
  Keywords  
  Abstract Salient object segmentation in videos is generally broken up in a video segmentation part and a saliency assignment part. Recently, object proposals, which are used to segment the image, have had significant impact on many computer vision applications, including image segmentation, object detection, and recently saliency detection in still images. However, their usage has not yet been evaluated for salient object segmentation in videos. Therefore, in this paper, we investigate the application of object proposals to salient object segmentation in videos. In addition, we propose a new motion feature derived from the optical flow structure tensor for video saliency detection. Experiments on two standard benchmark datasets for video saliency show that the proposed motion feature improves saliency estimation results, and that object proposals are an efficient method for salient object segmentation. Results on the challenging SegTrack v2 and Fukuchi benchmark data sets show that we significantly outperform the state-of-the-art.  
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  Area Expedition Conference  
  Notes LAMP; 600.120 Approved no  
  Call Number KAW2020 Serial 3504  
Permanent link to this record
 

 
Author (up) Rain Eric Haamer; Eka Rusadze; Iiris Lusi; Tauseef Ahmed; Sergio Escalera; Gholamreza Anbarjafari edit  doi
isbn  openurl
  Title Review on Emotion Recognition Databases Type Book Chapter
  Year 2018 Publication Human-Robot Interaction: Theory and Application Abbreviated Journal  
  Volume Issue Pages  
  Keywords emotion; computer vision; databases  
  Abstract Over the past few decades human-computer interaction has become more important in our daily lives and research has developed in many directions: memory research, depression detection, and behavioural deficiency detection, lie detection, (hidden) emotion recognition etc. Because of that, the number of generic emotion and face databases or those tailored to specific needs have grown immensely large. Thus, a comprehensive yet compact guide is needed to help researchers find the most suitable database and understand what types of databases already exist. In this paper, different elicitation methods are discussed and the databases are primarily organized into neat and informative tables based on the format.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-78923-316-2 Medium  
  Area Expedition Conference  
  Notes HUPBA; 602.133 Approved no  
  Call Number Admin @ si @ HRL2018 Serial 3212  
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Author (up) Rain Eric Haamer; Kaustubh Kulkarni; Nasrin Imanpour; Mohammad Ahsanul Haque; Egils Avots; Michelle Breisch; Kamal Nasrollahi; Sergio Escalera; Cagri Ozcinar; Xavier Baro; Ahmad R. Naghsh-Nilchi; Thomas B. Moeslund; Gholamreza Anbarjafari edit   pdf
doi  openurl
  Title Changes in Facial Expression as Biometric: A Database and Benchmarks of Identification Type Conference Article
  Year 2018 Publication 8th International Workshop on Human Behavior Understanding Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Facial dynamics can be considered as unique signatures for discrimination between people. These have started to become important topic since many devices have the possibility of unlocking using face recognition or verification. In this work, we evaluate the efficacy of the transition frames of video in emotion as compared to the peak emotion frames for identification. For experiments with transition frames we extract features from each frame of the video from a fine-tuned VGG-Face Convolutional Neural Network (CNN) and geometric features from facial landmark points. To model the temporal context of the transition frames we train a Long-Short Term Memory (LSTM) on the geometric and the CNN features. Furthermore, we employ two fusion strategies: first, an early fusion, in which the geometric and the CNN features are stacked and fed to the LSTM. Second, a late fusion, in which the prediction of the LSTMs, trained independently on the two features, are stacked and used with a Support Vector Machine (SVM). Experimental results show that the late fusion strategy gives the best results and the transition frames give better identification results as compared to the peak emotion frames.  
  Address Xian; China; May 2018  
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  ISSN ISBN Medium  
  Area Expedition Conference FGW  
  Notes HUPBA; no proj Approved no  
  Call Number Admin @ si @ HKI2018 Serial 3118  
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Author (up) Ramin Irani; Kamal Nasrollahi; Chris Bahnsen; D.H. Lundtoft; Thomas B. Moeslund; Marc O. Simon; Ciprian Corneanu; Sergio Escalera; Tanja L. Pedersen; Maria-Louise Klitgaard; Laura Petrini edit   pdf
doi  openurl
  Title Spatio-temporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition Type Conference Article
  Year 2015 Publication 2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) Abbreviated Journal  
  Volume Issue Pages 88-95  
  Keywords  
  Abstract Pain is a vital sign of human health and its automatic detection can be of crucial importance in many different contexts, including medical scenarios. While most available computer vision techniques are based on RGB, in this paper, we investigate the effect of combining RGB, depth, and thermal
facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain and recognizes between three intensity levels in 82% of the analyzed frames improving more than 6% over RGB only analysis in similar conditions.
 
  Address Boston; EEUU; June 2015  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference CVPRW  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ INB2015 Serial 2654  
Permanent link to this record
 

 
Author (up) Ramon Baldrich edit  openurl
  Title Perceptual approach to a computational colour-texture representation for surface inspection. Type Book Whole
  Year 2001 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
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  Notes CIC Approved no  
  Call Number CAT @ cat @ Bal2001 Serial 73  
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Author (up) Ramon Baldrich; Maria Vanrell; Robert Benavente; Anna Salvatella edit  openurl
  Title Color Enhancement based on perceptual sharpening Type Miscellaneous
  Year 2003 Publication Proceedings of the IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Barcelona  
  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 CIC Approved no  
  Call Number CAT @ cat @ BVB2003 Serial 370  
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Author (up) Ramon Baldrich; Ricardo Toledo; Ernest Valveny; Maria Vanrell edit  openurl
  Title Perceptual Colour Image Segmentation. Type Miscellaneous
  Year 2002 Publication Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002: 145–150. Abbreviated Journal  
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  Notes DAG;CIC;ADAS Approved no  
  Call Number CAT @ cat @ BTV2002 Serial 290  
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Author (up) Raquel Justo; Leila Ben Letaifa; Cristina Palmero; Eduardo Gonzalez-Fraile; Anna Torp Johansen; Alain Vazquez; Gennaro Cordasco; Stephan Schlogl; Begoña Fernandez-Ruanova; Micaela Silva; Sergio Escalera; Mikel de Velasco; Joffre Tenorio-Laranga; Anna Esposito; Maria Korsnes; M. Ines Torres edit  url
openurl 
  Title Analysis of the Interaction between Elderly People and a Simulated Virtual Coach, Journal of Ambient Intelligence and Humanized Computing Type Journal Article
  Year 2020 Publication Journal of Ambient Intelligence and Humanized Computing Abbreviated Journal AIHC  
  Volume 11 Issue 12 Pages 6125-6140  
  Keywords  
  Abstract The EMPATHIC project develops and validates new interaction paradigms for personalized virtual coaches (VC) to promote healthy and independent aging. To this end, the work presented in this paper is aimed to analyze the interaction between the EMPATHIC-VC and the users. One of the goals of the project is to ensure an end-user driven design, involving senior users from the beginning and during each phase of the project. Thus, the paper focuses on some sessions where the seniors carried out interactions with a Wizard of Oz driven, simulated system. A coaching strategy based on the GROW model was used throughout these sessions so as to guide interactions and engage the elderly with the goals of the project. In this interaction framework, both the human and the system behavior were analyzed. The way the wizard implements the GROW coaching strategy is a key aspect of the system behavior during the interaction. The language used by the virtual agent as well as his or her physical aspect are also important cues that were analyzed. Regarding the user behavior, the vocal communication provides information about the speaker’s emotional status, that is closely related to human behavior and which can be extracted from the speech and language analysis. In the same way, the analysis of the facial expression, gazes and gestures can provide information on the non verbal human communication even when the user is not talking. In addition, in order to engage senior users, their preferences and likes had to be considered. To this end, the effect of the VC on the users was gathered by means of direct questionnaires. These analyses have shown a positive and calm behavior of users when interacting with the simulated virtual coach as well as some difficulties of the system to develop the proposed coaching strategy.  
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  Notes HuPBA; no proj Approved no  
  Call Number Admin @ si @ JLP2020 Serial 3443  
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Author (up) Raul Chaves edit  openurl
  Title Sistema de identificacion mediante huellas dactilares Type Report
  Year 2004 Publication CVC Technical Report #81 Abbreviated Journal  
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  Address CVC (UAB)  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ Cha2004 Serial 507  
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