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Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa |
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Title |
A visible-Thermal Fusion based Monocular Visual Odometry |
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Conference Article |
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2015 |
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Iberian Robotics Conference (ROBOT 2015), International Conference on, Lisbon, Portugal, 2015 |
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417 |
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517-528 |
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Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion |
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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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English |
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English |
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no |
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cidis @ cidis @ |
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44 |
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Author |
Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos |
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Title |
A predictive model for human activity recognition by observing actions and context |
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Conference Article |
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2015 |
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ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015 |
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323 - 333 |
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Edge width, Image blu,r Defocus map, Edge model |
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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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no |
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cidis @ cidis @ |
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43 |
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Silva Steven, Paillacho Dennys, Verdezoto Nervo, Hernandez Juan David |
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Title |
TOWARDS ONLINE SOCIALLY ACCEPTABLE ROBOT NAVIGATION |
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Conference Article |
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2022 |
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IEEE INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING, |
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2022-August |
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707-714 |
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cidis @ cidis @ |
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199 |
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Patricia L. Suarez, Dario Carpio, Angel D. Sappa and Henry O. Velesaca |
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Title |
Transformer based Image Dehazing. |
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Conference Article |
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2022 |
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16TH International Conference On Signal Image Technology & Internet Based Systems SITIS 2022. |
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148-154 |
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cidis @ cidis @ |
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195 |
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