Methods for volume inference of non-medical objects from images: A short review

Baticté Nabitchita, N. Gonçalves, Paulo Jorge Simães Coelho, Luís Pimenta, Eftim Zdravevski, Petre Lameski, Mónica Costa, Paulo Alexandre Neves, Ivan Miguel Pires
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Abstract

Nowadays, the object’s volume is essential for monitoring any scene. Technological equipment is evolving, and mobile devices and other devices embed high-resolution cameras. The high-resolution cameras open a window for different research studies, where the volume measurement is vital for different areas. This study aims to identify image processing techniques for measuring the object’s volume. Thus, a systematic review was performed with a Natural Language Processing (NLP)-based framework for identifying studies between 2010 and 2023 related to the measurement of object volume. As a result of this search, this paper reviewed and analyzed 25 studies, verifying that different computer vision methods accurately handle object recognition. Additionally, an evaluation of the databases presented by the studies above is performed to consider further the design of a new approach to infer the volume of objects from an image.
从图像推断非医疗物体体积的方法:简评
如今,物体的体积对于监控任何场景都至关重要。技术设备在不断发展,移动设备和其他设备都嵌入了高分辨率摄像头。高分辨率照相机为不同领域的研究打开了一扇窗,在这些领域中,体积测量至关重要。本研究旨在确定测量物体体积的图像处理技术。因此,我们利用基于自然语言处理(NLP)的框架进行了一次系统性回顾,以确定 2010 年至 2023 年期间与物体体积测量相关的研究。经过搜索,本文对 25 项研究进行了回顾和分析,验证了不同的计算机视觉方法能够准确地识别物体。此外,本文还对上述研究提供的数据库进行了评估,以进一步考虑设计一种新方法,从图像中推断物体的体积。
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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