首页|Research Data from University of Granada Update Understanding of Machine Learnin g (Monocular visual SLAM, visual odometry, and structure from motion methods app lied to 3D reconstruction: A comprehensive survey)
Research Data from University of Granada Update Understanding of Machine Learnin g (Monocular visual SLAM, visual odometry, and structure from motion methods app lied to 3D reconstruction: A comprehensive survey)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news originating from Granada, Spain, by New sRx correspondents, research stated, “Monocular Simultaneous Localization and Ma pping (SLAM), Visual Odometry (VO), and Structure from Motion (SFM) are techniqu es that have emerged recently to address the problem of reconstructing objects o r environments using monocular cameras.” Our news correspondents obtained a quote from the research from University of Gr anada: “Monocular pure visual techniques have become attractive solutions for 3D reconstruction tasks due to their affordability, lightweight, easy deployment, good outdoor performance, and availability in most handheld devices without requ iring additional input devices. In this work, we comprehensively overview the SL AM, VO, and SFM solutions for the 3D reconstruction problem that uses a monocula r RGB camera as the only source of information to gather basic knowledge of this ill-posed problem and classify the existing techniques following a taxonomy. To achieve this goal, we extended the existing taxonomy to cover all the current c lassifications in the literature, comprising classic, machine learning, direct, indirect, dense, and sparse methods. We performed a detailed overview of 42 meth ods, considering 18 classic and 24 machine learning methods according to the ten categories defined in our extended taxonomy, comprehensively systematizing thei r algorithms and providing their basic formulations. Relevant information about each algorithm was summarized in nine criteria for classic methods and eleven cr iteria for machine learning methods to provide the reader with decision componen ts to implement, select or design a 3D reconstruction system.”
University of GranadaGranadaSpainE uropeCyborgsEmerging TechnologiesMachine Learning
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