Virtual Agent Positioning Driven by Personal Characteristics
Authors: 
Jingjing Liu, Youyi Zheng, Kun ZhouAuthors Info & Claims
Jingjing Liu, Youyi Zheng, Kun ZhouAuthors Info & ClaimsPages 7658 - 7666
Abstract
When people use agent characters to travel through different spaces (such as virtual scenes and real scenes, or different game spaces), it is important to reasonably position the characters in the new scene according to their personal characteristics. In this paper, we propose a novel pipeline for relocating virtual agents in new scenarios based on their personal characteristics. We extract the characteristics of the characters (including figure, posture, social distance). Then a cost function is designed to evaluate the agent's position in the scene, which consists of a spatial term and an personalized term. Finally, a a Markov Chain Monte Carlo optimization method is applied to search for the optimized solution. The results generated by our approach are evaluated through extensive user study experiments, verifying the effectiveness of our approach compared with other alternative approaches.
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Index Terms
- Virtual Agent Positioning Driven by Personal Characteristics
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October 2024
11719 pages
ISBN:9798400706868
DOI:10.1145/3664647
- General Chairs:
- Jianfei Cai,
- Mohan Kankanhalli,
- Balakrishnan Prabhakaran,
- Susanne Boll,
- Program Chairs:
- Ramanathan Subramanian,
- Liang Zheng,
- Vivek K. Singh,
- Pablo Cesar,
- Lexing Xie,
- Dong Xu
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Published: 28 October 2024
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