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Panoramic image stitching technology and its application in the field of autonomous driving
- 1 School of Engineering, The University of New South Wales, Sydney, Australia
* Author to whom correspondence should be addressed.
Abstract
Image processing technology is an indispensable part of the development of many fields, in which panoramic image stitching technology is one of the most widely used technologies in image processing, which is not only applied in the frontier fields of technology such as unmanned aerial vehicles and machine vision detection, but is also closely related to people's lives, for example, the panoramic camera shooting function of the smart phone. The driverless car is also a widely concerned field, its development means the liberation of manpower, the realization and improvement of self-driving car technology can alleviate traffic congestion, the use of transportation for people without the ability to drive and many other social problems. This paper will firstly introduce the panoramic collage technology, including its principle, system architecture and application prospect. Secondly, it focuses on the application of panoramic collage technology in the field of self-driving cars, which is divided into two aspects: sensor hardware and collocation algorithm, and analyzes the applicability of different algorithmic techniques in this field based on the demand characteristics of self-driving cars. The research in this paper points out the optimization direction of panoramic collage technology required by self-driving cars, which will be of great value to the development and application of panoramic collage technology in the field of self-driving cars.
Keywords
autonomous driving, panoramic image, image stitching, image processing technology
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Cite this article
Wang,Y. (2024). Panoramic image stitching technology and its application in the field of autonomous driving. Applied and Computational Engineering,31,284-289.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation
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