Selective Augmentation: A New Poetics for Computer Animation

Abstract

In this paper, we explore a concept for understanding computer-animated realism: selective augmentation. Selective augmentation, as a concept of animated realism, provides insight into the evolution of animation style and its effects on the spectator in the form of a stronger invitation to “mentalize” selectively augmented textures and characters. To demonstrate this point, we provide an outline of the current debate over animated realism as a concept; that is, can animation, a medium whose technology and practices often exclude it from the debates surrounding indexical reality, make a claim on any manner of realism? Far from being excluded from the realism debate, the author argues that animators often select certain materials or behaviors to highlight through formal techniques such as movement, textural detail, or color, thereby increasing their tangible credibility while simultaneously lessening their photoreality. The balance of cartoon abstraction with enough textural reality to encourage mentalizing and internal simulation in audience members forms the heart of modern computer-generated poetics, wherein spectators are encouraged through the formal properties of the animation to luxuriate in hyperreal depictions of fur, scales, textures, and detail that, while non-indexical, nevertheless grant audiences an opportunity to renew their appreciation for the everyday material spaces they inhabit. The author concludes by demonstrating how selective augmentation can provide critics and audiences with new insight into the effects of the formal properties of animation offers viewers non-indexical perspectives on reality in a way that nevertheless feels tangibly real.

Presenters

Nathan Snow
Associate Professor, Communication, Utah Tech University, Utah, United States

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

The Form of the Image

KEYWORDS

Animation, Materiality, Cinesthetics, Film, Cognition