YOLO多相机目标检测和距离估计

Bojan Strbac, Marko Gostovic, Ž. Lukač, D. Samardzija
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引用次数: 14

摘要

由于竞争激烈的市场要求和汽车行业软件的显著扩展,有必要和机会开发和实施新的算法和解决方案,这可以进一步提高这个快速增长和不断变化的行业的性能,功能和质量。本文的目的是提出使用相机代替激光雷达进行距离估计的可能性。该解决方案基于YOLO深度神经网络和立体原理。该解决方案使用两个稍微移动的相机获得两幅图像,并通过基于立体的测量算法。并估计到被检测物体的距离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
YOLO Multi-Camera Object Detection and Distance Estimation
Due to challenging requirements in the competitive market and significant software expansion in automotive industry, there is a need and opportunity to develop and implement new algorithms and solutions, which can further enhance performances, features and quality of this fast growing and constantly changing industry. The aim of this paper is to present the possibility of using cameras instead of LIDARs for distance estimation. The proposed solution is based on the YOLO deep neural network and principles of stereoscopy. This solution uses two slightly moved cameras which obtain two pictures, which goes through algorithm for stereoscopy-based measurement. And estimate distance to detected objects.
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