Reviewing Intelligent Cinematography: AI research for camera-based video production
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull

TL;DR
This comprehensive review explores AI techniques in camera-based video production, categorizing applications across different production types and highlighting trends, challenges, and ethical considerations impacting the creative industry.
Contribution
It provides the first holistic overview of intelligent cinematography, integrating technical insights and categorizing research in virtual, live, aerial, and general production contexts.
Findings
Virtual production has the highest potential impact.
AI techniques are advancing in camera calibration and content acquisition.
Ethical and legal issues are significant in AI-driven cinematography.
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…
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Taxonomy
Topics3D Modeling in Geospatial Applications
MethodsDiffusion
