Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/33511
Title: Methods for volume inference of non-medical objects from images: A short review
Authors: Nabitchita, Baticté
Gonçalves, Norberto Jorge
Coelho, Paulo Jorge
Pimenta, Luís
Zdravevski, Eftim 
Lameski, Petre 
Costa, Mónica
Neves, Paulo Alexandre
Pires, Ivan Miguel
Issue Date: 17-Jan-2024
Publisher: SAGE Publications
Journal: Journal of Ambient Intelligence and Smart Environments
Abstract: <jats:p>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.</jats:p>
URI: http://hdl.handle.net/20.500.12188/33511
DOI: 10.3233/ais-230193
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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