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Author | Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa | ||||
Title | A visible-Thermal Fusion based Monocular Visual Odometry | Type | Conference Article | ||
Year | 2015 | Publication | Iberian Robotics Conference (ROBOT 2015), International Conference on, Lisbon, Portugal, 2015 | Abbreviated Journal | |
Volume | 417 | Issue | Pages | 517-528 | |
Keywords | Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion | ||||
Abstract | The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained representations are evaluated under a visual odometry framework, highlighting their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach. | ||||
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Language | English | Summary Language | English | Original Title | |
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Call Number | cidis @ cidis @ | Serial | 44 | ||
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Author | Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos | ||||
Title | A predictive model for human activity recognition by observing actions and context | Type | Conference Article | ||
Year | 2015 | Publication | ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015 | Abbreviated Journal | |
Volume | Issue | Pages | 323 - 333 | ||
Keywords | Edge width, Image blu,r Defocus map, Edge model | ||||
Abstract | This paper presents a novel model to estimate human activities – a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach. | ||||
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Call Number | cidis @ cidis @ | Serial | 43 | ||
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Author | Angel D. Sappa. | ||||
Title | ICT Applications for Smart Cities | Type | Book Chapter | ||
Year | 2022 | Publication | Intelligent Systems Reference Library | Abbreviated Journal | BOOK |
Volume | 224 | Issue | Pages | ||
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Call Number | cidis @ cidis @ | Serial | 198 | ||
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Author | Michael Teutsch, Angel Sappa & Riad Hammoud | ||||
Title | Computer Vision in the Infrared Spectrum: Challenges and ApproachesComputer Vision in the Infrared Spectrum: Challenges and Approaches | Type | Journal Article | ||
Year | 2021 | Publication | Synthesis Lectures on Computer Vision | Abbreviated Journal | |
Volume | Vol. 10 No. 2 | Issue | Pages | pp. 138 | |
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Call Number | cidis @ cidis @ | Serial | 166 | ||
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Author | Silva Steven, Paillacho Dennys, Verdezoto Nervo, Hernandez Juan David | ||||
Title | TOWARDS ONLINE SOCIALLY ACCEPTABLE ROBOT NAVIGATION | Type | Conference Article | ||
Year | 2022 | Publication | IEEE INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING, | Abbreviated Journal | |
Volume | 2022-August | Issue | Pages | 707-714 | |
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Call Number | cidis @ cidis @ | Serial | 199 | ||
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Author | Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. | ||||
Title | LDC: Lightweight Dense CNN for Edge Detection. | Type | Journal Article | ||
Year | 2022 | Publication | IEEE Access journal | Abbreviated Journal | |
Volume | Vol. 10 | Issue | Pages | pp. 68281-68290 | |
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Call Number | cidis @ cidis @ | Serial | 183 | ||
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Author | Pereira J., Mora M. & W. Agila | ||||
Title | Qualitative Model to Maximize Shrimp Growth at Low Cost | Type | Journal Article | ||
Year | 2021 | Publication | 5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 | Abbreviated Journal | |
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Call Number | cidis @ cidis @ | Serial | 167 | ||
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Author | Patricia L. Suarez, Dario Carpio, Angel D. Sappa and Henry O. Velesaca | ||||
Title | Transformer based Image Dehazing. | Type | Conference Article | ||
Year | 2022 | Publication | 16TH International Conference On Signal Image Technology & Internet Based Systems SITIS 2022. | Abbreviated Journal | |
Volume | Issue | Pages | 148-154 | ||
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Call Number | cidis @ cidis @ | Serial | 195 | ||
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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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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Adaptive Harris Corners Detector Evaluated with Cross-Spectral Images | Type | Conference Article | ||
Year | 2018 | Publication | International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing | Abbreviated Journal | |
Volume | 721 | Issue | Pages | ||
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Abstract | This paper proposes a novel approach to use cross-spectral images to achieve a better performance with the proposed Adaptive Harris corner detector comparing its obtained results with those achieved with images of the visible spectra. The images of urban, field, old-building and country category were used for the experiments, given the variety of the textures present in these images, with which the complexity of the proposal is much more challenging for its verification. It is a new scope, which means improving the detection of characteristic points using crossspectral images (NIR, G, B) and applying pruning techniques, the combination of channels for this fusion is the one that generates the largest variance based on the intensity of the merged pixels, therefore, it is that which maximizes the entropy in the resulting Cross-spectral images. Harris is one of the most widely used corner detection algorithm, so any improvement in its efficiency is an important contribution in the field of computer vision. The experiments conclude that the inclusion of a (NIR) channel in the image as a result of the combination of the spectra, greatly improves the corner detection due to better entropy of the resulting image after the fusion, Therefore the fusion process applied to the images improves the results obtained in subsequent processes such as identification of objects or patterns, classification and/or segmentation. |
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Notes | 1 | Approved | no | ||
Call Number | gtsi @ user @ | Serial | 84 | ||
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