中文摘要：

目的 针对背投式多投影系统中存在的各向异性问题,提出一套行之有效的解决方案.方法 首先,为了解决以静态观众为主体的多投影系统各向异性问题,基于反馈机制提出了以特定位置为中心的“最佳观测域”,并在该区域内实现了真正的视觉无缝画面校正;然后,基于视觉人体跟踪技术进一步提出了以特定交互者为中心的“动态最佳观测域”框架,并结合模糊预测控制思想从人体重心检测、跟踪和投影仪亮度实时补偿等3个方面对该框架内的各个组成模块的关键技术进行了阐述.结果 实验结果显示,利用交互者运动的时空连续性优化后的动态最佳观测域算法,具有较好的鲁棒性和实时性.同时,与其他类似方法相比获得了更好的视觉无缝校正效果,其中观测距离为1 m、3m和5m时,对应的亮度样本标准差分别为17.11、13.17和9.2.结论 提出的各向异性解决方案,将实时反馈信号引入校正过程中,有效提高了输出画面质量.通过实验测试和性能评估,验证了文中方法的可行性.

英文摘要：

Objective Large-scale multi-projector display systems offer high resolution, high brightness, a large field of view, and a compelling sense of presence. Thus, these systems have been considered effective choices to tackle the conflict between the increasing demands for super-resolution display and the resolution limitations of single display equipment. However, the display color and brightness of these systems show significant spatial variation, which can be very distracting, there by breaking the illusion of a single display. Furthermore, the use of the rear projection mode has serious an isotropy problems; in particular, the brightness of the projected image varies in accordance with the location of the observer. In this paper, we propose an effective solution to solve the an isotropy problem of rear-projection multi-projector tiled display walls. Method Our solution includes two levels： static and dynamic optimal observation districts. The static optimal observation district method is focused on situations with a small amount of audience who only moves in a small area. Geometry and color calibrations are executed in accordance with a predetermined observation point by utilizing an information processing model of human attention. Subsequently, observers in the neighborhood of the observation point can see calibrated images with highly visual seamless effects. To relax the restrictions of the moving range, we present an observer-centered framework for the dynamic optimal observation district by integrating human tracking techniques and fuzzy predictive control algorithms. In this framework, we first optimize the process of creating projector models and color look-up tables. The cente positions of the target observer are then computed viavideo-based object tracking. Finally, fuzzy predictive control algorithms are used to deal with the positions to create step-shaped coordinates for the human body center, there by minimizing the need to adjust the brightness compensation and to speed up the screen calibration.