基于计算机视觉的射箭光学

Atul Raj
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引用次数: 0

摘要

今天,射箭被用于体育运动、狩猎、娱乐射击、电影等。传统的瞄准镜会因振动而失去对准,需要工具调零,调整耗时,在某些背景下难以看清,并且受视差的影响。为了克服这些挑战,开发了一款基于计算机视觉的智能手机瞄准应用程序。该应用程序的特点是数字瞄准,调零,箭头下降调零,没有任何工具,基于背景的十字线颜色反转,基于传感器的倾斜水平指示器,变焦,和归零距离自动保存。这些功能的目的是提高可视性,易于调整,瞄准没有任何额外的成本。接下来,对瞄准系统的性能进行了测试,由一名弓箭手向一个50厘米的目标射箭。在3天的清晨,总共有37枪在外面射击。使用新瞄准具,第1天的平均绝对误差为10.85,第2天的平均绝对误差为7.18,第3天的平均绝对误差为6.25。由于很难找到另一位熟练的弓箭手,这项研究的样本量很小,因为射箭不是一项常见的运动,而且有很大的学习曲线。目前的研究确定了基于计算机视觉增强的实用性和效率,如数字瞄准、快速归零和更好的可视性。此外,在未来,其他研究可以在智能手机应用程序中使用人工智能、机器学习和基于传感器的风向预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer Vision-Based Archery Optics

Today, archery is used in sports, hunting, recreational shooting, movies, etc. Traditional sights can lose alignment due to vibration and require tools for zeroing, are time-consuming for adjustment, difficult to see in certain backgrounds, and are affected by parallax. To overcome these challenges, a computer vision-based aiming application for smartphones was developed. The features of this application are digital aiming, zeroing, and arrow drop zeroing without any tools, background-based reticle color inversion, sensor-based incline level indicator, zoom, and zeroed distance autosave. These features aim to improve visibility, ease of adjustment, and aiming without any additional cost. Next, the performance of the sight system was tested by an archer firing arrows at a 50 cm target. A total number of 37 shots were fired outside on 3 days, early morning. By using the new sight, a mean absolute error of 10.85 on day 1, 7.18 on day 2, and 6.25 on day 3 was obtained. The study was limited by a small sample size due to difficulty in finding another skilled archer, as archery is not a common sport and has a huge learning curve. The current study identifies the practicality and efficiency of computer vision-based augmentation, like digital aiming, fast zeroing, and better visibility. Additionally, in future, other studies can work on the use of AI, ML, and sensor-based wind direction prediction in a smartphone application.

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