From Camera-Eye to AI: Exploring the Interplay of Cinematography and Computational Visual Storytelling

要旨

While much prior work on computational visual storytelling analyzes image content, it largely overlooks formal elements. This raises the question: how might particular cinematographic techniques shape a system's interpretation and narration of imagery? To investigate this question, we generate 60 responses from a Vision Language Model using a multi-faceted prompt paired with different still frames from Man with a Movie Camera (1929), a silent documentary film renowned for its innovative cinematography. We present three themes that highlight roles of cinematography in computational visual storytelling: (1) how AI discerns drama and power from camera shots and angles that portray social reality; (2) how AI (mis)interprets lighting and focus techniques that compose ambiguous reality; and (3) how AI navigates visual effects that render surreality. In turn, we look toward cinematic controls to reimagine users as directors of visual storytelling systems and discuss how expressive AI can support speculating about the past.

著者
Brett A.. Halperin
University of Washington, Seattle, Washington, United States
Stephanie M. Lukin
U.S. Army Research Laboratory, Playa Vista, California, United States
DOI

10.1145/3706598.3713840

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713840

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Digital Storytelling

G304
7 件の発表
2025-04-29 01:20:00
2025-04-29 02:50:00
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