Collective Crowd Formation Transform with Mutual Information–Based Runtime Feedback. (18th August 2014)

• Record Type: Journal Article
• Authors: Xu, Mingliang; Wu, Yunpeng; Ye, Yangdong; Farkas, Illes; Jiang, Hao; Deng, Zhigang
• Is Part Of: Computer graphics forum. Volume 34:Number 1(2015)
• Page Start: 60
• Page End: 73
• Publication Date: 2014-08-18
• Subjects: Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12459
• Languages: English
• ISSNs: 0167-7055

Abstract

<abstract abstract-type="graphical" xml:lang="en" id="cgf12459-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>This paper introduces a new crowd formation transform approach to achieve visually pleasing group formation transition and control. Its core idea is to transform crowd formation shapes with a least‐effort pair assignment using the Kuhn–Munkres algorithm, discover clusters of agent subgroups using affinity propagation and Delaunay triangulation algorithms, and apply subgroup‐based SFM (social force model) to the agent subgroups to achieve alignment, cohesion and collision avoidance. <boxed-text content-type="graphic" position="anchor" orientation="portrait"><graphic position="anchor" mimetype="image" xlink:href="ark:/27927/pgj1v6f13s" orientation="portrait" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink" /></boxed-text></p> </abstract>