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      Ortomosaicos y modelos digitales de elevación generados a partir de imágenes tomadas con sistemas UAV Translated title: Orthomosaics and digital elevation models generated from images taken with UAV systems

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          Abstract

          RESUMEN Contexto: Actualmente, los vehículos aéreos no tripulados (UAV por su sigla en inglés) son una de las herramientas tecnológicas de mayor investigación y aplicación en áreas como la fotogrametría aérea y de percepción remota, presentándose como una importante alternativa para la captura de imágenes de alta resolución espacial y temporal. Sin embargo, las características de vuelo, de las imágenes y de los sensores utilizados en los UAV generan grandes desafíos en el procesamiento tradicional para la generación de productos cartográficos como modelos digitales de elevación y ortomosaicos, por lo que se requiere de la identificación de nuevas estrategias de procesamiento. Método: En el presente artículo se realiza una revisión bibliográfica de las principales características de los UAV empleados en fotogrametría aérea junto con las estrategias de procesamiento afines que actualmente se están empleando en áreas como visión por computador y fotogrametría. Resultados: A partir de la revisión se observa que las estrategias de procesamiento en el área de visión por computador son más afines con la información capturada con los sistemas UAV para la generación de modelos digitales de elevación y ortomosaicos. Conclusiones: Los adelantos tecnológicos de los sistemas UAV y los avances en las estrategias de procesamiento de grandes volúmenes de datos seguirán impulsando la investigación y aplicación de estos sistemas en áreas como la fotogrametría y visión por computador, para la generación de productos cartográficos de mayor precisión.

          Translated abstract

          ABSTRACT Context: Nowadays, Unmanned Aerial Vehicles (UAVs) are among the technological tools most researched and applied in areas such as aerial photogrammetry and remote sensing, presenting itself as an important alternative for capturing imagery with high spatial and temporal resolution. However, UAV flight parameters, image and sensor characteristics, result on major challenges for traditional processing for producing mapping products such as digital elevation models and orthomosaics, that is why it is required to identify new processing strategies. Method: In this paper, a review of the main characteristics of UAVs used in aerial photogrammetry is done, along with related processing strategies currently being used in areas such as computer vision and photogrammetry. Results: From this review, it is shown that processing strategies in the area of computer vision are more akin to the information captured with UAV systems for generating digital elevation models and orthomosaics. Conclusions: The technological advances in UAVs systems and advances in strategies for processing large data volumes continue to drive research and application of these systems for the generation of mapping products more accurately in areas such as photogrammetry and computer vision.

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          Most cited references92

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          Object recognition from local scale-invariant features

          D.G. Lowe (1999)
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            Performance evaluation of local descriptors.

            In this paper, we compare the performance of descriptors computed for local interest regions, as, for example, extracted by the Harris-Affine detector. Many different descriptors have been proposed in the literature. It is unclear which descriptors are more appropriate and how their performance depends on the interest region detector. The descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the detector. Our evaluation uses as criterion recall with respect to precision and is carried out for different image transformations. We compare shape context, steerable filters, PCA-SIFT, differential invariants, spin images, SIFT, complex filters, moment invariants, and cross-correlation for different types of interest regions. We also propose an extension of the SIFT descriptor and show that it outperforms the original method. Furthermore, we observe that the ranking of the descriptors is mostly independent of the interest region detector and that the SIFT-based descriptors perform best. Moments and steerable filters show the best performance among the low dimensional descriptors.
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              Unmanned aerial systems for photogrammetry and remote sensing: A review

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                tecn
                Tecnura
                Tecnura
                Universidad Distrital Francisco José de Caldas (Bogotá, Distrito Capital, Colombia )
                0123-921X
                December 2016
                : 20
                : 50
                : 119-140
                Affiliations
                [02] Bucaramanga orgnameUniversidad Industrial de Santander Colombia jcaceres@ 123456uis.edu.co
                [03] Bucaramanga orgnameUniversidad Industrial de Santander Colombia hporras@ 123456uis.edu.co
                [01] Bucaramanga orgnameUniversidad Industrial de Santander Colombia jescalto@ 123456uis.edu.co
                Article
                S0123-921X2016000400009
                10.14483/udistrital.jour.tecnura.2016.4.a09
                78741dc0-1b6a-43c3-ad61-cff75ddb416d

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 08 February 2016
                : 10 September 2016
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 95, Pages: 22
                Product

                SciELO Colombia


                imágenes aéreas,aerial images,DSM,orthomosaic,point clouds,UAV,MDE,nube de puntos,ortomosaicos

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