江苏大学学报（自然科学版）2011，Vol.32Issue(4)：385-388,473,5.DOI:10.3969/j.issn.1671-7775.2011.04.003
基于空间信息高斯混合模型的运动车辆检测
Moving vehicle detection method based on Gaussian mixture model of spatial information
摘要
Abstract
By using conventional Gaussian mixture model, moving object was always detected incorrectly for the situation of dynamic variation of background image and scene, because only pixel level and time domain were classified regardless of spatial information. Based on spatial neighborhood weighted Gaussian mixture model, a moving vehicle detection method was proposed. According to spatial feature of pixel, a spatial information function was defined to restrain noisy. The neighbor information weighted class probabilities of very pixels with spatial constraint were designed and proved to be meet with two criterions of normalization and spatial continuity. Regarding space and time information, the iterative renovated parameter formula and the moving detection algorithm were proposed. The experiments of moving vehicle detection for urban traffic video sequences under different climate demonstrate that the proposed method can get better classification effeciency and accuracy with low misjudgement rate.关键词
智能交通系统/运动目标/检测/高斯混合模型/空间信息Key words
intelligent transportation systems/ moving object/ detection/ Gaussian mixture model/ spatial information分类
交通工程引用本文复制引用
张晓娜,何仁,刘志强,陈士安,倪捷..基于空间信息高斯混合模型的运动车辆检测[J].江苏大学学报（自然科学版）,2011,32(4):385-388,473,5.基金项目
江苏省博士生创新基金资助项目(CX09B-205Z) （CX09B-205Z）
江苏省自然科学基金资助项目(BK2008553) （BK2008553）
