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Avoiding obstacles in Underwater Glider Path Planning
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por Antonio C. Domínguez Brito
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publicado
26/11/2012
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Última modificación
26/11/2012 17:23
Ubicado en
Publicaciones / Publications
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Reducción de Errores de Odometría en un Robot Móvil utilizando Algoritmos de Scan Matching basados en Sensores de Rango
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por Antonio C. Domínguez Brito
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publicado
26/11/2012
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Última modificación
26/11/2012 17:26
Ubicado en
Publicaciones / Publications
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A Component-Based C++ Communication Middleware for an Autonomous Robotic Sailboat
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por Antonio C. Domínguez Brito
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publicado
10/12/2019
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Última modificación
10/12/2019 13:47
The new C++ standard, C++11, and its upgrade, C++14, introduces new advances and features which make more affordable and easier the development of software for complex systems. Following this tenet we have designed and developed a component-based service-oriented C++ middleware, called ISE, for distributed systems using exclusively standard C++ and the quasi standard C++ Boost Libraries for keeping the middleware portable. The final aim of developing ISE has been to build the remote communication software infrastructure of an oceanic autonomous robotic sailboat called A-Tirma.
Ubicado en
Publicaciones / Publications
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Airflow dynamics, vegetation and aeolian erosive processes in a shadow zone leeward of a resort in an arid transgressive dune system
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por Antonio C. Domínguez Brito
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publicado
10/12/2019
Structures and infrastructures can modify aeolian sedimentary dynamics as has occurred in the arid transgressive dunefield of Maspalomas (Gran Canaria, Canary Islands), where an aeolian shadow zone has been formed leeward of a tourist resort (Playa del Inglés). The aim of this paper is to analyse spatial and statistically the influences of vegetation and topography on wind flow across this shadow zone. An experiment was carried out in March 2017, collecting wind speed and direction from 5 transects with anemometers at 0.40 m height. Simultaneously, a drone flight was carried out, from which an orthophoto and digital elevation and surface models (DEM and DSM) were obtained. Distance from the resort, and the presence of vegetation were found to influence transects dominated by erosional processes. Transects that do not display erosional processes were primarily affected by the presence of vegetation. The local wind field changes at a similar distance across the transects downwind from the resorts indicating an acceleration or reattachment of the wind at this distance downwind. The vegetation role in this aeolian shadow zone could be a key to the future evolution of the area resulting in either further stabilization, or alternatively, the continued deflation of the area.
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Publicaciones / Publications
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Acoustic Detection of Tagged Angelsharks from an Autonomous Sailboat
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por Antonio C. Domínguez Brito
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publicado
10/12/2019
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Última modificación
21/12/2019 14:38
Autonomous sailboats are silent surface vehicles which are well suited for acoustic monitoring. The integration of an acoustic receiver in an unmanned surface vehicle has a large potential for population monitoring as it permits to report geo-referenced detections in real time, so that researchers can adapt monitoring strategies as data arrive. In this paper we present preliminary work, done on the framework of ACUSQUAT project, to explore the usage of an acoustic receiver onboard a small (2 m length-over-all) autonomous sailboat in order to detect the presence of tagged adult exemplars of angelshark (Squatina squatina), the target species in ACUSQUAT, in certain areas which have demonstrated that this approach is feasible. Results obtained in simulation and during field trials are presented.
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Publicaciones / Publications
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ILRA: Novelty Detection in Face-Based Intervener Re-Identification
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por Antonio C. Domínguez Brito
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publicado
20/12/2019
Transparency laws facilitate citizens to monitor the activities of political representatives. In this sense, automatic or manual diarization of parliamentary sessions is required, the latter being time consuming. In the present work, this problem is addressed as a person re-identification problem. Re-identification is defined as the process of matching individuals under different camera views. This paper, in particular, deals with open world person re-identification scenarios, where the captured probe in one camera is not always present in the gallery collected in another one, i.e., determining whether the probe belongs to a novel identity or not. This procedure is mandatory before matching the identity. In most cases, novelty detection is tackled applying a threshold founded in a linear separation of the identities. We propose a threshold-less approach to solve the novelty detection problem, which is based on a one-class classifier and therefore it does not need any user defined threshold. Unlike other approaches that combine audio-visual features, an Isometric LogRatio transformation of a posteriori (ILRA) probabilities is applied to local and deep computed descriptors extracted from the face, which exhibits symmetry and can be exploited in the re-identification process unlike audio streams. These features are used to train the one-class classifier to detect the novelty of the individual. The proposal is evaluated in real parliamentary session recordings that exhibit challenging variations in terms of pose and location of the interveners. The experimental evaluation explores different configuration sets where our system achieves significant improvement on the given scenario, obtaining an average F measure of 71.29% for online analyzed videos. In addition, ILRA performs better than face descriptors used in recent face-based closed world recognition approaches, achieving an average improvement of 1.6% with respect to a deep descriptor.
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Publicaciones / Publications
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A semantic parliamentary multimedia approach for retrieval of video clips with content understanding
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por Antonio C. Domínguez Brito
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publicado
20/12/2019
Digital videos of parliamentary activity play an important role in enhancing transparency and accountability for open e-government. The rapid growth in these videos and the lack of semantic annotations and relationships between video and knowledge resources make it increasingly difficult to find accurate video clips with contextual information for content understanding. To overcome this problem, we highlight the need for building multimedia systems based on a semantic vision. With this aim, we focus on (1) how to address the knowledge representation for automatic extraction of contextual information for video content understanding; (2) how to link the parliamentary knowledge structures within video resources to provide accurate video clips retrieval; and (3) how to perform semantic annotation on video resources. The methodology applied is focused on a systematic approach that uses techniques from ontology engineering. This approach is based on the definition of two models: the semantic model and the reference architecture. The semantic model is composed of a reference ontology and a semantic video annotation framework. The ontology provides the support for video content understanding and the semantic vocabulary for annotating video resources. The video annotation framework is based on an RDF-powered semantic video annotation to effectively relate low- and mid-level visual features, corresponding to speakers’ interventions, to high-level parliamentary concepts. To evaluate the proposed system, a prototype for the Canary Islands Parliament (Spain) has been carried out. The results show how semantic enhancement is a key enabler for improved video retrieval on parliamentary multimedia content.
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Publicaciones / Publications
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Deep learning for source camera identification on mobile devices
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por Antonio C. Domínguez Brito
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publicado
20/12/2019
In the present paper, we propose a source camera identification (SCI) method for mobile devices based on deep learning. Recently, convolutional neural networks (CNNs) have shown a remarkable performance on several tasks such as image recognition, video analysis or natural language processing. A CNN consists on a set of layers where each layer is composed by a set of high pass filters which are applied all over the input image. This convolution process provides the unique ability to extract features automatically from data and to learn from those features. Our proposal describes a CNN architecture which is able to infer the noise pattern of mobile camera sensors (also known as camera fingerprint) with the aim at detecting and identifying not only the mobile device used to capture an image (with a 98% of accuracy), but also from which embedded camera the image was captured. More specifically, we provide an extensive analysis on the proposed architecture considering different configurations. The experiment has been carried out using the images captured from different mobile device cameras (MICHE-I Dataset) and the obtained results have proved the robustness of the proposed method.
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Publicaciones / Publications
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Success history applied to expert system for underwater glider path planning using differential evolution
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por Antonio C. Domínguez Brito
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publicado
20/12/2019
This paper presents an application of a recently well performing evolutionary algorithm for continuous numerical optimization, Success-History Based Adaptive Differential Evolution Algorithm (SHADE) including Linear population size reduction (L-SHADE), to an expert system for underwater glider path planning (UGPP). The proposed algorithm is compared to other similar algorithms and also to results from literature. The motivation of this work is to provide an alternative to the current glider mission control systems, that are based mostly on multidisciplinary human-expert teams from robotic and oceanographic areas. Initially configured as a decision-support expert system, the natural evolution of the tool is targeting higher autonomy levels. To assess the performance of the applied optimizers, the test functions for UGPP are utilized as defined in literature, which simulate real-life oceanic mission scenarios. Based on these test functions, in this paper, the performance of the proposed application of L-SHADE to UGPP is aggregated using statistical analyis. The depicted fitness convergence graphs, final obtained fitness plots, trajectories drawn, and per-scenario analysis show that the new proposed algorithm yields stable and competitive output trajectories. Over the set of benchmark missions, the newly obtained results with a configured L-SHADE outperforms existing literature results in UGPP and ranks best over the compared algorithms. Moreover, some additional previously applied algorithms have been reconfigured to yield improved performance. Thereby, this new application of evolutionary algorithms to UGPP contributes significantly to the capacity of the decision-makers, when they use the improved UGPP expert system yielding better trajectories.
Ubicado en
Publicaciones / Publications
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ACUSQUAT Project: Acoustic behavioural monitoring of the Angelshark (Squatina squatina) in critical conservation areas
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por Antonio C. Domínguez Brito
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publicado
20/01/2020
Ubicado en
Publicaciones / Publications
Instituto Un
Universidad de Las Palmas de Gran Canaria