Methods for Processing and Understanding Image Sequences in Autonomous Navigation Problems

IF 0.7 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2023-12-01 DOI:10.1134/s1054661823040156

引用次数: 0

Abstract

This article presents the results of research into methods and algorithms for processing image sequences aimed at application in autonomous navigation systems. The methods are grouped in the following areas: pre-processing, generation of 2D and 3D scene models, object recognition. and determination of motion parameters from a sequence of images. The article presents methods and algorithms proposed and researched by the authors of the article over the past decade. Description of the methods and algorithms is accompanied by examples and results of experimental studies.

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处理和理解自主导航问题中图像序列的方法

摘要本文介绍了旨在应用于自主导航系统的图像序列处理方法和算法的研究成果。这些方法分为以下几个方面：预处理、生成二维和三维场景模型、物体识别以及根据图像序列确定运动参数。文章介绍了作者在过去十年中提出和研究的方法和算法。在介绍方法和算法的同时，还提供了实验研究的实例和结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

PATTERN RECOGNITION AND IMAGE ANALYSIS Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

1.80

自引率

20.00%

发文量

期刊介绍： The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.