JOURNAL ARTICLE
The point cloud aesthetic: Defining a new visual language in media art.
Published In: Virtual Creativity, 2023, v. 13, n. 2. P. 213 1 of 3
Database: Art Source Ultimate 2 of 3
Authored By: Ivsic, Lucija; McCormack, Jon; Dziekan, Vince 3 of 3
Abstract
This article examines the emergence of point clouds—3D datasets generated by remote sensing technologies such as Light Detection and Ranging (LiDAR) and photogrammetry—as a new digital art medium with a distinctive visual language. It identifies four key aesthetic elements of point cloud artworks: subject matter derived from scanned real-world objects or environments, transparency reflecting the dissolution of forms into data points, ambiguity arising from technical artefacts or scanning 'glitches,' and algorithmic shaping through digital manipulation and immersive technologies like virtual reality. Through analysis of selected works by artists Stefano Caimi, Quayola, and Dan Holdsworth, the article traces the medium's progression from precise scientific representation toward expressive, posthuman perspectives that foreground the machine's 'eye' view. It concludes that point clouds have evolved into a multifaceted artistic medium that challenges traditional notions of representation and offers new creative possibilities within digital art.
Additional Information
- Source:Virtual Creativity. 2023/12, Vol. 13, Issue 2, p213
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2023
- ISSN:2397-9704
- DOI:10.1386/vcr_00085_1
- Accession Number:178503613
- Copyright Statement:Copyright of Virtual Creativity is the property of Intellect Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.