Real-time online learning of Gaussian mixture model for opacity mapping

doi:10.1016/j.neucom.2015.12.135

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Real-time online learning of Gaussian mixture model for opacity mapping
	Zhou, Guo 1,2,3; Zhu, Dengming 1,2; Wei, Yi 1,2; Wang, Zhaoqi 1,2; Zhou, Yongquan 4
刊名	NEUROCOMPUTING
	2016-10-26
卷号	211 页码:212-220
关键词	Participating media Online expectation-maximization Shadow Order-independent transparency
ISSN号	0925-2312
DOI	10.1016/j.neucom.2015.12.135
英文摘要	Rendering volumetric scattering in real-time is a challenge due to the complex interactions between the light and the particles in the participating media. Assuming that a ray leaving the emitter is scattered only once along its path to the sensor, we propose to represent the extinction coefficient by a Gaussian mixture model. Then the model is trained with a large number of particles colliding that ray in an online way. A low-cost updating function based on the weighted maximum likelihood estimation is derived for the weighted stepwise expectation-maximization algorithm, which is fitted into the graphics pipeline as a stage of learning. This enables all those particles to contribute to the extinction on the fly without storing and sorting them together with respect to the emitter in a geometry pass. Our approach is able to accurately reconstruct the per-pixel transmittance of the opacity map for optically thick heterogeneous media in real-time but operate in bounded memory, using the recently introduced fragment shader critical section feature of the graphics processing unit. (C) 2016 Elsevier B.V. All rights reserved.
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000384871700023
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/7970]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhou, Guo
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Guo,Zhu, Dengming,Wei, Yi,et al. Real-time online learning of Gaussian mixture model for opacity mapping[J]. NEUROCOMPUTING,2016,211:212-220.
APA	Zhou, Guo,Zhu, Dengming,Wei, Yi,Wang, Zhaoqi,&Zhou, Yongquan.(2016).Real-time online learning of Gaussian mixture model for opacity mapping.NEUROCOMPUTING,211,212-220.
MLA	Zhou, Guo,et al."Real-time online learning of Gaussian mixture model for opacity mapping".NEUROCOMPUTING 211(2016):212-220.