三峡大学学报（自然科学版）2012，Vol.34Issue(6)：98-102,5.
基于改进K均值的运动目标检测算法研究
An Approach Based on Modified K-means for Moving Objects Detection
摘要
Abstract
A key issue of detecting moving objects, an approach based on modified K-means to model background is proposed. It learns from the starting N frames with K-means algorithm; and the results learned the background of the pixels. Following, it performs the separation of background pixels, probable foreground pixels and shadow pixels; through the comparison of the input pixels and the background model, a pixel-based selective mechanism of the background update is proposed. Finally, the ghost effects are eliminated by applying the TOM method. The experimental results show that this proposed approach can well model the background, and more accurately extract the moving objects, as well as more robust to the illumination changes.关键词
K均值聚类/背景减除/运动目标检测Key words
K-means clusters background subtraction/moving objects detection分类
信息技术与安全科学引用本文复制引用
柯尊海,刘勇,徐义春,雷帮军..基于改进K均值的运动目标检测算法研究[J].三峡大学学报（自然科学版）,2012,34(6):98-102,5.基金项目
湖北省自然科学基金(2011CDB180) （2011CDB180）
