基于无人机视觉的深度学习森林人体目标检测

S. Yong, Y. Yeong
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引用次数: 27

摘要

在过去的十年中,各种令人印象深刻的新应用已经在无人机上开发和实施,例如搜索和救援,监视,交通监控,天气监测等等。当前无人机技术的进步引发了重大变化,使无人机能够以越来越复杂的水平执行广泛的任务。搜索和救援或森林监视等任务需要较大的相机覆盖范围,因此使无人机成为执行高级任务的合适工具。同时,计算机视觉中深度学习应用的增长趋势也为这个项目的主动性提供了一个显著的洞察。本文提出了一种基于深度学习框架的人类目标检测算法来检测森林环境中人类存在的技术。探测林区人类存在的目的是为了减少非法进入禁区、非法采伐等非法林业活动。此外,预计该项目的成果将扩大无人机在森林监视方面的使用,以节省时间和成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human Object Detection in Forest with Deep Learning based on Drone’s Vision
In the past decade, various new and impressive applications have been developed and implemented on drones, for instance search and rescue, surveillance, traffic monitoring, weather monitoring and so on. The current advances in drone technology provoked significant changes in enabling drones to perform a wide range of missions with increasing level of complexity. Missions such as search and rescue or forest surveillance require a large camera coverage and thus making drone a suitable tool to perform advanced tasks. Meanwhile, the increasing trend of deep learning applications in computer vision provides a remarkable insight into the initiative of this project. This paper presents a technique which allows detecting the existence of human in forestry environment with human object detection algorithm using deep learning framework. The purpose of detecting human existence in forestry area is to reduce illegal forestry activities such as illegal entry into prohibited area and illegal logging activities. Also, the outcome of this project is expected to aggrandize the usage of drone for forest surveillance purpose to save time and cost.
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