GPU BASED VIDEO STYLIZATION

摘要：

In this paper, we present a GPU based video stylization framework that can artistically stylize video stream in real time. In this framework, firstly, we use a separable implementation of bilateral filter as an adaptive and iterative smoothing operation that selectively simplifies image color, leading to an abstracted look. Secondly, we perform a soft color quantization step on the abstracted video. A significant advantage of the soft color quantization implementation is preserving temporal coherence and reducing computation time as well. Successively, some optional approaches are designed to generate different artistic styles. We evaluate the effectiveness of our stylization framework with the experiment results.

关键词： GPU Video srylization NPR

作者: YANG ZHAO DENG-EN XIE DAN XU

作者单位: Department of Computer Science, Yunnan University, Kunming, 650091, China Department of Computer Sci Department of Computer Science, Yunnan University, Kunming, 650091, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2880-2885

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）