An Object-Driven Collision Detection with 2D Cameras using Artificial Intelligence and Computer Vision

Yang Liu, Evan Gunnell, Yu Sun, Hao Zheng
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Abstract

Autonomous driving is one of the most popular technologies in artificial intelligence. Collision detection is an important issue in automatic driving, which is related to the safety of automatic driving. Many collision detection methods have been proposed, but they all have certain limitations and cannot meet the requirements for automatic driving. Camera is one of the most popular methods to detect objects. The obstacle detection of the current camera is mostly completed by two or more cameras (binocular technology) or used in conjunction with other sensors (such as a depth camera) to achieve the purpose of distance detection. In this paper, we propose an algorithm to detect obstacle distances from photos or videos of a single camera.
基于人工智能和计算机视觉的二维相机对象驱动碰撞检测
自动驾驶是人工智能领域最受欢迎的技术之一。碰撞检测是自动驾驶中的一个重要问题,它关系到自动驾驶的安全性。目前已经提出了许多碰撞检测方法,但它们都有一定的局限性,不能满足自动驾驶的要求。相机是最常用的物体检测方法之一。当前摄像机的障碍物检测多由两个或多个摄像机(双目技术)完成,或与其他传感器(如深度摄像机)配合使用,以达到距离检测的目的。在本文中,我们提出了一种从单个相机的照片或视频中检测障碍物距离的算法。
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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