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Video-Based Crowd Synthesis

机译：基于视频的人群综合

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As a controllable medium, video-realistic crowds are important for creating the illusion of a populated reality in special effects, games, and architectural visualization. While recent progress in simulation and motion captured-based techniques for crowd synthesis has focused on natural macroscale behavior, this paper addresses the complementary problem of synthesizing crowds with realistic microscale behavior and appearance. Example-based synthesis methods such as video textures are an appealing alternative to conventional model-based methods, but current techniques are unable to represent and satisfy constraints between video sprites and the scene. This paper describes how to synthesize crowds by segmenting pedestrians from input videos of natural crowds and optimally placing them into an output video while satisfying environmental constraints imposed by the scene. We introduce crowd tubes, a representation of video objects designed to compose a crowd of video billboards while avoiding collisions between static and dynamic obstacles. The approach consists of representing crowd tube samples and constraint violations with a conflict graph. The maximal independent set yields a dense constraint-satisyfing crowd composition. We present a prototype system for the capture, analysis, synthesis, and control of video-based crowds. Several results demonstrate the system's ability to generate videos of crowds which exhibit a variety of natural behaviors.
机译：作为一种可控制的媒介，具有视频现实感的人群对于在特殊效果，游戏和建筑可视化中营造出一个充满现实感的幻觉至关重要。尽管基于模拟和基于运动捕捉的人群综合技术的最新进展集中在自然宏行为上，但本文解决了具有现实的微观行为和外观的人群合成的补充问题。基于示例的合成方法（例如视频纹理）是传统的基于模型的方法的一种有吸引力的替代方法，但是当前的技术无法表示和满足视频子画面和场景之间的约束。本文介绍了如何通过将自然人群的输入视频中的行人进行分割，并在满足场景所施加的环境约束的同时，将其最佳地放置到输出视频中来合成人群。我们介绍了人群管，它是视频对象的一种表示形式，旨在组成大量视频广告牌，同时避免静态和动态障碍物之间发生碰撞。该方法包括用冲突图表示拥挤试管样本和约束违例。最大独立集产生密集的约束满足人群组成。我们提出了一个用于捕获，分析，合成和控制基于视频的人群的原型系统。几个结果证明了该系统生成具有各种自然行为的人群视频的能力。

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