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| Author | Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla | ||||
| 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 | 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. |
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| Call Number | cidis @ cidis @ | Serial | 169 | ||
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| Author | Cristhian A. Aguilera; Cristhian Aguilera; Angel D. Sappa | ||||
| Title | Melamine faced panels defect classification beyond the visible spectrum. | Type | Journal Article | ||
| Year | 2018 | Publication | In Sensors 2018 | Abbreviated Journal | |
| Volume | Vol. 11 | Issue | Issue 11 | Pages | |
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| Abstract | In this work, we explore the use of images from different spectral bands to classify defects in melamine faced panels, which could appear through the production process. Through experimental evaluation, we evaluate the use of images from the visible (VS), near-infrared (NIR), and long wavelength infrared (LWIR), to classify the defects using a feature descriptor learning approach together with a support vector machine classifier. Two descriptors were evaluated, Extended Local Binary Patterns (E-LBP) and SURF using a Bag of Words (BoW) representation. The evaluation was carried on with an image set obtained during this work, which contained five different defect categories that currently occurs in the industry. Results show that using images from beyond the visual spectrum helps to improve classification performance in contrast with a single visible spectrum solution. |
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| Call Number | gtsi @ user @ | Serial | 89 | ||
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| Author | Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa | ||||
| Title | Fine-tuning deep convolutional networks for lepidopterous genus recognition | Type | Journal Article | ||
| Year | 2017 | Publication | Lecture Notes in Computer Science | Abbreviated Journal | |
| Volume | Vol. 10125 LNCS | Issue | Pages | pp. 467-475 | |
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| Call Number | gtsi @ user @ | Serial | 63 | ||
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| Author | Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo | ||||
| Title | Cross-Spectral Local Descriptors via Quadruplet Network | Type | Journal Article | ||
| Year | 2017 | Publication | In Sensors Journal | Abbreviated Journal | |
| Volume | Vol. 17 | Issue | Pages | pp. 873 | |
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| Call Number | gtsi @ user @ | Serial | 64 | ||
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| Author | Victor Santos; Angel D. Sappa; Miguel Oliveira | ||||
| Title | Special Issue on Autonomous Driving an Driver Assistance Systems | Type | Journal Article | ||
| Year | 2017 | Publication | In Robotics and Autonomous Systems Journal | Abbreviated Journal | |
| Volume | Vol. 91 | Issue | Pages | pp. 208-209 | |
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| Call Number | gtsi @ user @ | Serial | 65 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture | Type | Conference Article | ||
| Year | 2017 | Publication | 19th International Conference on Image Analysis and Processing. | Abbreviated Journal | |
| Volume | Issue | Pages | 287-297 | ||
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| Call Number | gtsi @ user @ | Serial | 66 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Learning Image Vegetation Index through a Conditional Generative Adversarial Network | Type | Conference Article | ||
| Year | 2017 | Publication | 2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) | Abbreviated Journal | |
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| Call Number | gtsi @ user @ | Serial | 70 | ||
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| Author | Xavier Soria; Angel D. Sappa; Arash Akbarinia | ||||
| Title | Multispectral Single-Sensor RGB-NIR Imaging: New Challenges an Oppotunities | Type | Conference Article | ||
| Year | 2017 | Publication | The 7th International Conference on Image Processing Theory, Tools and Application | Abbreviated Journal | |
| Volume | Issue | Pages | 1-6 | ||
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| Call Number | gtsi @ user @ | Serial | 72 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud | ||||
| Title | Deep Learning based Single Image Dehazing | Type | Conference Article | ||
| Year | 2018 | Publication | 14th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2018. Salt Lake City, Utah. USA | Abbreviated Journal | |
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| Abstract | This paper proposes a novel approach to remove haze degradations in RGB images using a stacked conditional Generative Adversarial Network (GAN). It employs a triplet of GAN to remove the haze on each color channel independently. A multiple loss functions scheme, applied over a conditional probabilistic model, is proposed. The proposed GAN architecture learns to remove the haze, using as conditioned entrance, the images with haze from which the clear images will be obtained. Such formulation ensures a fast model training convergence and a homogeneous model generalization. Experiments showed that the proposed method generates high-quality clear images. |
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| Call Number | gtsi @ user @ | Serial | 83 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Vegetation Index Estimation from Monospectral Images | Type | Conference Article | ||
| Year | 2018 | Publication | 15th International Conference, Image Analysis and Recognition (ICIAR 2018), Póvoa de Varzim, Portugal. Lecture Notes in Computer Science | Abbreviated Journal | |
| Volume | 10882 | Issue | Pages | 353-362 | |
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| Abstract | This paper proposes a novel approach to estimate Normalized Difference Vegetation Index (NDVI) from just the red channel of a RGB image. The NDVI index is defined as the ratio of the difference of the red and infrared radiances over their sum. In other words, information from the red channel of a RGB image and the corresponding infrared spectral band are required for its computation. In the current work the NDVI index is estimated just from the red channel by training a Conditional Generative Adversarial Network (CGAN). The architecture proposed for the generative network consists of a single level structure, which combines at the final layer results from convolutional operations together with the given red channel with Gaussian noise to enhance details, resulting in a sharp NDVI image. Then, the discriminative model estimates the probability that the NDVI generated index came from the training dataset, rather than the index automatically generated. Experimental results with a large set of real images are provided showing that a Conditional GAN single level model represents an acceptable approach to estimate NDVI index. |
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| Call Number | gtsi @ user @ | Serial | 82 | ||
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