On Developing a Particle System Driven by Computer Vision Modules
Date Issued
2008
Date
2008
Author(s)
Huang, Wei-Jia
Abstract
Vision based interaction devices are getting more and more popular in recent years. Applications for these devices that can give users interesting interaction experiences and rich visual appearances are also on demand. In our work, we develop a particle system that can be driven by computer vision modules. It is easy to be integrated into other computer vision applications and provides varieties of visual effects and interactions to the users. On the other hand, results of computer vision process usually have some degrees of uncertainty. Our particle system also supplies a new way to visualize the fuzzy region by the motion of particles. In this paper, we introduce three integration examples, including a vision-based multi-touch tabletop system called i-m-Top, a multi-camera surveillance system with view transition, and an intelligent computer-aided Tai Chi Chuan learning system. All these three applications can be easily integrated with our particle system. To increase the system performance, we utilize the latest generation of graphic process unit (GPU) to implement our particle system. This implementation not only enlarges the number of particles we can simulate in real time, but also reserves the CPU computation power for the computer vision process. In addition, we propose an inter-particle collision detection method that estimates the spatial density distribution of particles by statistic method. Inter-particle collision responses are then computed according to the density distribution. This method makes particles have behaviors similar to the Brownian motion and can be done by GPU very efficiently.
Subjects
Particle System
Computer vision
GPGPU
Type
thesis
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