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Author N. Onkarappa; Cristhian A. Aguilera; B. X. Vintimilla; Angel D. Sappa pdf  url
openurl 
  Title Cross-spectral Stereo Correspondence using Dense Flow Fields Type Conference Article
  Year 2014 Publication Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 Abbreviated Journal  
  Volume 3 Issue Pages (up) 613 - 617  
  Keywords Cross-spectral Stereo Correspondence, Dense Optical Flow, Infrared and Visible Spectrum  
  Abstract This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach.  
  Address  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference 2014 International Conference on Computer Vision Theory and Applications (VISAPP)  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 27  
Permanent link to this record
 
 
Author Rafael E. Rivadeneira, Angel D. Sappa and Boris X. Vintimilla pdf  openurl
  Title Multi-Image Super-Resolution for Thermal Images. Type Conference Article
  Year 2022 Publication Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 Abbreviated Journal  
  Volume 4 Issue Pages (up) 635 - 642  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 181  
Permanent link to this record
 
 
Author Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla pdf  openurl
  Title Human Pose Estimation through A Novel Multi-View Scheme Type Conference Article
  Year 2022 Publication Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 Abbreviated Journal  
  Volume 5 Issue Pages (up) 855-862  
  Keywords Multi-View Scheme, Human Pose Estimation, Relative Camera Pose, Monocular Approach  
  Abstract This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human

pose estimation problem. The proposed approach first obtains the human body joints of a set of images,

which are captured from different views at the same time. Then, it enhances the obtained joints by using a

multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from

another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed

for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and

comparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements

in the accuracy of body joints estimations.		  
  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 Approved yes  
  Call Number cidis @ cidis @ Serial 169  
Permanent link to this record
 
 
Author Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title Cross-Spectral Local Descriptors via Quadruplet Network Type Journal Article
  Year 2017 Publication In Sensors Journal Abbreviated Journal  
  Volume Vol. 17 Issue Pages (up) pp. 873  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 64  
Permanent link to this record
 
 
Author Armin Mehri; Angel D. Sappa pdf  openurl
  Title Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples Type Conference Article
  Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal  
  Volume Issue Pages (up) 971-979  
  Keywords  
  Abstract This paper presents a novel approach for colorizing

near infrared (NIR) images. The approach is based on

image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored

networks that require less computation times, converge

faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation

metrics—and qualitatively evaluated showing considerable

improvements with respect to the state of the art		  
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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  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 105  
Permanent link to this record
 
 
Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud pdf  openurl
  Title Image Vegetation Index through a Cycle Generative Adversarial Network Type Conference Article
  Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal  
  Volume Issue Pages (up) 1014-1021  
  Keywords  
  Abstract This paper proposes a novel approach to estimate the

Normalized Difference Vegetation Index (NDVI) just from

an RGB image. The NDVI values are obtained by using

images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The

cycled GAN network is able to obtain a NIR image from

a given gray scale image. It is trained by using unpaired

set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are

obtained from the provided RGB images). Then, the NIR

image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous

approaches are also provided.		  
  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 Approved no  
  Call Number gtsi @ user @ Serial 106  
Permanent link to this record
 
 
Author Xavier Soria, Yachuan Li, Mohammad Rouhani & Angel D. Sappa pdf  openurl
  Title Tiny and Efficient Model for the Edge Detection Generalization Type Conference Article
  Year 2023 Publication Proceedings – 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023 Abbreviated Journal  
  Volume Issue Pages (up) 1356 - 1365  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 229  
Permanent link to this record
 
 
Author Xavier Soria; Edgar Riba; Angel D. Sappa pdf  isbn
openurl 
  Title Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection Type Conference Article
  Year 2020 Publication 2020 IEEE Winter Conference on Applications of Computer Vision (WACV) Abbreviated Journal  
  Volume Issue 9093290 Pages (up) 1912-1921  
  Keywords  
  Abstract This paper proposes a Deep Learning based edge de- tector, which is inspired on both HED (Holistically-Nested Edge Detection) and Xception networks. The proposed ap- proach generates thin edge-maps that are plausible for hu- man eyes; it can be used in any edge detection task without previous training or fine tuning process. As a second contri- bution, a large dataset with carefully annotated edges, has been generated. This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons. Quantitative and qualitative evaluations have been performed on different benchmarks showing im- provements with the proposed method when F-measure of ODS and OIS are considered.  
  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 978-172816553-0 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 126  
Permanent link to this record
 
 
Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud pdf  openurl
  Title Near InfraRed Imagery Colorization Type Conference Article
  Year 2018 Publication 25 th IEEE International Conference on Image Processing, ICIP 2018 Abbreviated Journal  
  Volume Issue Pages (up) 2237-2241  
  Keywords  
  Abstract This paper proposes a stacked conditional Generative

Adversarial Network-based method for Near InfraRed

(NIR) imagery colorization. We propose a variant architecture

of Generative Adversarial Network (GAN) that uses multiple

loss functions over a conditional probabilistic generative model.

We show that this new architecture/loss-function yields better

generalization and representation of the generated colored IR

images. The proposed approach is evaluated on a large test

dataset and compared to recent state of the art methods using

standard metrics.1

Index Terms—Convolutional Neural Networks (CNN), Generative

Adversarial Network (GAN), Infrared Imagery colorization.		  
  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 Approved no  
  Call Number gtsi @ user @ Serial 81  
Permanent link to this record
 
 
Author M. Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel D. Sappa; A. Tomé pdf  url
openurl 
  Title Concurrent Learning of Visual Codebooks and Object Categories in Open- ended Domains Type Conference Article
  Year 2015 Publication Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, Hamburg, Germany, 2015 Abbreviated Journal  
  Volume Issue Pages (up) 2488 - 2495  
  Keywords Birds, Training, Legged locomotion, Visualization, Histograms, Object recognition, Gaussian mixture model  
  Abstract In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are usually constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using codebooks constructed offline.  
  Address  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Hamburg, Germany Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 41  
Permanent link to this record
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