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Author |
Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa |
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Title |
Feature Point Descriptors: Infrared and Visible Spectra |
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Journal Article |
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2014 |
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Sensors Journal |
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Vol. 14 |
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pp. 3690-3701 |
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cross-spectral imaging; feature point descriptors |
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This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given. |
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no |
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cidis @ cidis @ |
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28 |
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Author |
Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla |
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Title |
Deep learning-based vegetation index estimation |
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2021 |
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Generative Adversarial Networks for Image-to-Image Translation Book. |
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Chapter 9 |
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Issue 2 |
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205-232 |
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no |
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cidis @ cidis @ |
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137 |
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Author |
Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla |
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Title |
Human Pose Estimation through A Novel Multi-View Scheme |
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Conference Article |
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Year |
2022 |
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Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 |
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5 |
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855-862 |
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Keywords |
Multi-View Scheme, Human Pose Estimation, Relative Camera Pose, Monocular Approach |
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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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yes |
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cidis @ cidis @ |
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169 |
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Author |
Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic |
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Title |
Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles |
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2016 |
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Journal of Automation and Control Engineering (JOACE) |
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Vol. 4 |
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pp. 430-436 |
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Keywords |
Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System |
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Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset. |
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cidis @ cidis @ |
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51 |
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