Contribution to a conference proceedings

DZNE-2022-01063

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Using Discrete Time Markov Chains for Control of Idle Character Animation

Streck, A. (First author)DZNE* ; Wolbers, T. (Last author)DZNE*

2018
IEEE

This record in other databases:  

Please use a persistent id in citations: doi:10.1109/CIG.2018.8490450

Abstract: The behavior of autonomous characters in virtual environments is usually described via a complex deterministic state machine or a behavior tree driven by the current state of the system. This is very useful when a high level of control over a character is required, but it arguably does have a negative effect on the illusion of realism in the decision making process of the character. This is particularly prominent in cases where the character only exhibits idle behavior, e.g. a student sitting in a classroom. In this article we propose the use of discrete time Markov chains as the model for defining realistic non-interactive behavior and describe how to compute decision probabilities to normalize by the length of individual actions. Lastly, we argue that those allow for more precise calibration and adjustment for the idle behavior model then the models being currently employed in practice.

---

Contributing Institute(s):

1. Aging, Cognition and Technology (AG Wolbers)

Research Program(s):

1. 344 - Clinical and Health Care Research (POF3-344) (POF3-344)

Appears in the scientific report 2018

---