Remote sensing of the earth and monitoring of various phenomena have been and still remain an important task for solving various problems. One of them is the forest pathology dynamics determining. Assuming its dependence on various factors forest pathology can be either short-term or long-term. Sometimes it is necessary to analyze satellite images within a period of several years in order to determine the dynamics of forest pathology. So it is connected with some special aspects and makes such analysis in manual mode impossible. At the same time automated methods face the problem of identifying a series of suitable images even though they are not covered by clouds, shadows, turbulence and other distortions. Classical methods of nebulosity determination based either on neural network or decision functions do not always give an acceptable result, because the cloud coverage by itself can be either of cirrus intortus type or insignificant within the image, but in case of cloudiness it can be the reason for wrong analysis of the area under examination. The article proposes a new approach for the analysis and selection of images based on key point detectors connected neither with cloudiness determination nor distorted area identification, but with the extraction of suitable images eliminating those that by their characteristics are unfit for forest pathology determination. Experiments have shown that the accuracy of this approach is higher than of currently used method in GIS, which is based on cloud detector.
The monocular visual odometry algorithm involves several basic steps and for each of them there is a number of methods. The purpose of this work is to conduct practical research of methods for key point detection and the optical flow calculation in the problem of determining the unmanned ground vehicle proper motion. For detection method research conduction the image panel containing various distortions typical for follow robot shot was made. It has been educed that among the accounted methods FAST finds the largest number of points within the minimum elapsed time. At the same time image distortions strongly affect the results of the method, which is negative for the positioning of the robot. Therefore the Shi-Tomasi method was chosen for key points detection within a short period of time, because its results are less dependent on distortion. For research undertake a number of video clips by means of the follow robot shot was made in a confined space at a later scale of the odometry algorithm. From experimental observations the conclusions concerning the application of Lucas-Kanade optical flow method tracking the identified points on the video sequence have been made. Based on the error in the results obtained it was implication that monocular odometry cannot be the main method of an unmanned vehicle positioning in confined spaces, but in combination with probe data given by assistive sensors it is quite possible to use it for determining the robotic system position.
This paper describes general approach to the space-time mathematical model in motions of mobile objects. The efficacy and performance of these approaches in monitoring system and basic algorithms were investigated. The choice of modeling approach motion trajectories for some initial conditions was proved
Изучено одно из актуальных направлений в области больших данных -обработка многомерной информации. Рассмотрена одна из возможных структур данных -многомерная пирамида, которая позволяет выполнять многие операции над данны-ми со сложностью O(1) либо O(logn). Приведены описание, анализ и оценка эффективности много-мерной пирамиды.Ключевые слова: многомерная пирамида, базовые операции, разновидности k-d пирамид, улучшение k-d пирамид, большая размерность дан-ных. ASSESSMENT OF MULTIDIMENSIONAL PYRAMID EFFICIENCYThe paper deals with one of the urgent trends in the field of big data -multidimensional information processing. One of possible data structures -multidimensional pyramid which allows fulfilling many operations with the complexity O(1) or O(logn) is under consideration. For basic operations there are given thorough examples. The description, analysis and assessment of multidimensional pyramid efficiency are shown. The assessments of operation complexity with these data depending upon their dimensionality are given. The analysis of multidimensional pyramid efficiency for its different modifications is shown.Key words: multidimensional pyramid, basic operations, sorts of k-d pyramids, k-d pyramid improvement, data large dimensionality. ВведениеВ настоящее время в мире активно ведутся работы по проблеме больших дан-ных (Big Data). Трудности связаны не только с большим объёмом данных, но и со сложностью объектов данных и их взаимоотношениями.Объекты с многочисленными пара-метрами далеко не всегда можно свести к одному параметру с помощью свёртки ли-бо уменьшения размерности объекта [2]. Альтернативой в этом случае является применение многомерной модели данных [1]. Отношения между данными сущест-венно влияют на время выполнения основ-ных операций над ними. Если алгоритм часто использует операции «вставить», «найти максимум/минимум», «удалить максимум/минимум», «удалить заданный элемент», «изменить заданный элемент» и некоторые другие, то здесь весьма удоб-ными являются пирамидальные структуры данных [3]. Они позволяют выполнять большинство операций за один шаг, т.е. практически не зависят от размерности за-дачи, либо имеют логарифмическую слож-ность (в худшем случае). Одной из таких структур является многомерная пирамида.Для эффективного представления многомерной приоритетной очереди ис-пользуется k-d пирамида [7]. Базовая фор-ма k-d пирамиды не использует дополни-тельного пространства, требует линейного времени на построение, логарифмического времени для вставки, удаления или изме-нения любого элемента очереди и обеспе-чивает постоянную сложность доступа к элементам, содержащим минимальный ключ любого измерения. Более того, струк-тура может быть расширена до многомер-ной двусторонней приоритетной очереди. Для некоторых приложений оптимальным вариантом будут многомерные приоритет-ные очереди.После разработки единой структуры отпала необходимость в дополнительной памяти для хранения связей, дополнитель-ных операциях для поддержки различных приоритетных отношений. При использо-вании неявного представления k-d пира-...
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