Papers

@article{Figuero2018240,

title = {Dynamical study of a moored vessel using computer vision},

author = {Andrés Figuero-Pérez and Álvaro Rodríguez and José Sande-González-Cela and Enrique Peña-González and Juan R. Rabuñal-Dopico},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048929421&doi=10.6119%2fJMST.2018.04_%282%29.0011&partnerID=40&md5=5ac71a51e7d6a9857551b9ea6c40b8d2},

doi = {10.6119/JMST.2018.04_(2).0011},

issn = {10232796},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Journal of Marine Science and Technology (Taiwan)},

volume = {26},

number = {2},

pages = {240-250},

publisher = {National Taiwan Ocean University},

abstract = {Wind and wave effects have a major impact on the design of mooring and anchoring systems, whose purpose is to prevent the movement of the cargo and the moored ship while optimizing the operations which have to take place in port. The dynamic behavior of a ship moored in waves has been mathematically described and interactions between ships and environmental loads have been commonly tested for different docks and mooring systems in scale models. However, the behavior of real ships in true mooring conditions has not been properly addressed in scientific literature. This paper proposes a novel computer vision technique to monitor moored ships. This approach uses the correlation of visual features in the images of the ship to estimate its movements along time. The proposed technique has been validated in laboratory conditions and applied in a real scenario to study the behavior of the ship Urania Mella in the Outer Port of A Coruña (Spain), in Punta Langosteira, obtaining very promising results. © National Taiwan Ocean University. All rights reserved.},

note = {cited By 12},

keywords = {Anchoring systems; Block Matching; Computer vision techniques; Dynamic behaviors; Environmental loads; Laboratory conditions; Scientific literature; Ship motion, Computer vision, Mooring; Ships; Uranium dioxide},

pubstate = {published},

tppubtype = {article}

}

@article{Rico-Diaz2015218,

title = {A detection system for vertical slot fishways using laser technology and computer vision techniques},

author = {Ángel J. Rico-Díaz and Álvaro Rodríguez and Daniel Villares-Budiño and Juan R. Rabuñal-Dopico and Jerónimo Puertas-Agudo and Luis Pena-Mosquera},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937469118&doi=10.1007%2f978-3-319-19258-1_19&partnerID=40&md5=5472196946c593e370a5082cd1b95903},

doi = {10.1007/978-3-319-19258-1_19},

issn = {03029743},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {9094},

pages = {218-226},

publisher = {Springer Verlag},

abstract = {Vertical slot fishways are structures that are placed in rivers to allow fish to avoid obstacles such as dams, hydroelectric plants. Knowing the frequency with which fish go through this type of structures can help to determine their efficiency, as well as know migratory features from species, determine if the fluvial course is healthy or if it is possible to fish with fauna preservation guarantees. A non-invasive method for fish detection, without the need of direct observation, which uses a laser sensor and computer vision techniques to detect fish, is proposed in this work. © Springer International Publishing Switzerland 2015.},

note = {cited By 5},

keywords = {Artificial intelligence; Fish; Fisheries; Fishways; Neural networks; Noninvasive medical procedures, Computer vision, Computer vision techniques; Detection system; Direct observations; Hydroelectric plant; Laser detection; Laser technologies; Noninvasive methods; Vertical slot fishways},

pubstate = {published},

tppubtype = {article}

}

@article{Rodriguez2011257,

title = {Study of strength tests with computer vision techniques},

author = {Álvaro Rodríguez and Juan R. Rabuñal-Dopico and Juan Luis Pérez-Ordóñez and Fernando Martínez-Abella},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956296419&doi=10.1007%2f978-3-642-21326-7_28&partnerID=40&md5=9e45b9ff4e22364d7d59a020a6997eaf},

doi = {10.1007/978-3-642-21326-7_28},

issn = {03029743},

year  = {2011},

date = {2011-01-01},

urldate = {2011-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {6687 LNCS},

number = {PART 2},

pages = {257-266},

abstract = {Knowing the strain response of materials in strength tests is one of the main issues in construction and engineering fields. In these tests, information about displacements and strains is usually carried out using physical devices attached to the material. In this paper, the suitability of Computer Vision techniques to analyse strength tests without interfering with the assay is discussed and a new technique is proposed. This technique measures displacements and deformations from a video sequence of the assay. With this purpose a Block-Matching Optical Flow algorithm is integrated with a calibration process to extract the vectorfield from the displacement in the material. To evaluate the proposed technique, a synthetic image set and a real sequence from a strength tests were analysed. © 2011 Springer-Verlag Berlin Heidelberg.},

note = {cited By 2},

keywords = {Block Matching; Calibration process; Computer vision techniques; Engineering fields; Optical flow algorithm; Physical devices; Strain response; Strength Tests; Synthetic images; Technique measures; Video sequences, Computer vision, Image matching; Optical flows; Strain; Testing},

pubstate = {published},

tppubtype = {article}

}

@article{Iglesias20091073,

title = {Computer vision applied to wave flume measurements},

author = {Gregorio Iglesias and Óscar Ibáñez and Alberte Castro and Juan R. Rabuñal-Dopico and Julián Dorado},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-69949099782&doi=10.1016%2fj.oceaneng.2009.06.012&partnerID=40&md5=6b3b127fc5cc72205466211d8a59bbd7},

doi = {10.1016/j.oceaneng.2009.06.012},

issn = {00298018},

year  = {2009},

date = {2009-01-01},

urldate = {2009-01-01},

journal = {Ocean Engineering},

volume = {36},

number = {14},

pages = {1073-1079},

abstract = {A new measurement system for laboratory wave flumes is presented, based on the analysis of digital images by means of computer vision techniques. Unlike conventional wave gauges, the system detects the motions of the free surface along the flume section of interest as opposed to a point. A further advantage lies in that no sensors are necessary within the flume. The system is particularly useful in the case of wave flume tests of floating bodies, such as an oil boom-the motions of the model boom are measured without any sensors in contact with it, which otherwise might place constraints on its displacements. The new method is validated based on free surface measurements carried out with a conventional wave gauge, with excellent results. © 2009 Elsevier Ltd. All rights reserved.},

note = {cited By 14},

keywords = {computer simulation; digital image; flume experiment; image processing; laboratory method; model validation; numerical model; surface wave; wave height; wave modeling, Computer vision, Computer vision techniques; Digital image; Floating bodies; Free surfaces; Measurement system; Measuring techniques; NO sensor; Video-image processing; Wave flumes, Fluid dynamics; Gages; Imaging systems; Sensors; Surface measurement; Surface waves; Water waves},

pubstate = {published},

tppubtype = {article}

}