Content area

Abstract

This paper offers the first comprehensive review of artificial intelligence (AI) research in the context of real camera content acquisition for entertainment purposes and is aimed at both researchers and cinematographers. Addressing the lack of review papers in the field of intelligent cinematography} (IC) and the breadth of related computer vision research, we present a holistic view of the IC landscape while providing technical insight, important for experts across disciplines. We provide technical background on generative AI, object detection, automated camera calibration and 3-D content acquisition, with references to assist non-technical readers. The application sections categorize work in terms of four production types: General Production, Virtual Production, Live Production and Aerial Production. Within each application section, we (1) sub-classify work according to research topic and (2) describe the trends and challenges relevant to each type of production. In the final chapter, we address the greater scope of IC research and summarize the significant potential of this area to influence the creative industries sector. We suggest that work relating to virtual production has the greatest potential to impact other mediums of production, driven by the growing interest in LED volumes/stages for in-camera virtual effects (ICVFX) and automated 3-D capture for virtual modeling of real world scenes and actors. We also address ethical and legal concerns regarding the use of creative AI that impact on artists, actors, technologists and the general public.

Details

1009240
Business indexing term
Title
Reviewing Intelligent Cinematography: AI research for camera-based video production
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 23, 2024
Section
Computer Science
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-24
Milestone dates
2024-05-08 (Submission v1); 2024-12-23 (Submission v2)
Publication history
 
 
   First posting date
24 Dec 2024
ProQuest document ID
3052863530
Document URL
https://www.proquest.com/working-papers/reviewing-intelligent-cinematography-ai-research/docview/3052863530/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-25
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic