Visual Computing for Autonomous Driving

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING IEEE Computer Graphics and Applications Pub Date : 2024-06-21 DOI:10.1109/mcg.2024.3397581

Siming Chen, Liang Gou, Michael Kamp, Dong Sun

引用次数: 0

Abstract

Autonomous driving (AD) technology has experienced unprecedented growth in recent years, propelled by advancements in artificial intelligence. The transition from theoretical concepts to tangible implementations of self-driving cars holds immense promise in revolutionizing transportation, with the potential to significantly reduce traffic accidents and associated costs. However, despite this rapid progress, the field still grapples with underutilization of the vast datasets generated by autonomous vehicles, particularly in the realm of visualization and visual analytics, or in a broader sense, visual computing.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

用于自动驾驶的视觉计算

近年来，在人工智能进步的推动下，自动驾驶（AD）技术经历了前所未有的发展。自动驾驶汽车从理论概念到实际应用的转变为交通领域带来了巨大的变革前景，有可能显著减少交通事故和相关成本。然而，尽管进展迅速，该领域仍然面临着自动驾驶汽车产生的大量数据集利用不足的问题，尤其是在可视化和可视分析领域，或者从广义上说，可视计算领域。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

IEEE Computer Graphics and Applications 工程技术-计算机：软件工程

CiteScore

3.20

自引率

5.60%

发文量

160

审稿时长

>12 weeks

期刊介绍： IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics, visualization, virtual and augmented reality, and HCI. From specific algorithms to full system implementations, CG&A offers a unique combination of peer-reviewed feature articles and informal departments. Theme issues guest edited by leading researchers in their fields track the latest developments and trends in computer-generated graphical content, while tutorials and surveys provide a broad overview of interesting and timely topics. Regular departments further explore the core areas of graphics as well as extend into topics such as usability, education, history, and opinion. Each issue, the story of our cover focuses on creative applications of the technology by an artist or designer. Published six times a year, CG&A is indispensable reading for people working at the leading edge of computer-generated graphics technology and its applications in everything from business to the arts.

期刊最新文献

PerSiVal: On-Body AR Visualization of Biomechanical Arm Simulations. Effect of white matter uncertainty visualization in neurosurgical decision making. Quantum Machine Learning Playground Q-Seg: Quantum Annealing-Based Unsupervised Image Segmentation BRPVis: Visual Analytics for Bus Route Planning Based on Perception of Passenger Travel Demand.