摘要
构建了基于块区域二阶矩比的三帧差分运动检测模型,应用文献[1]中的核密度估计模型来滤除其中的非运动区域,并采用支持向量聚类实现多目标检测。给出了运动物体轮廓快速追踪的RW算法,该算法不必考虑检测区域内部的细节问题,能够充分利用所检测到的边缘信息,比较符合人眼对轮廓的搜索习惯。最后给出了实验结果。
In the first section, according to the assumption that only the silhouette could be extracted to describe the motion of a moving object, a three-frame differencing model is constructed based on the variance ratio of successive blocks of different frames, simultaneously the Gaussian kernel based density estimation model in [1] is used as a filter to suppress false positives, and the SVC algorithm in [10] is also employed to realize real-time multi-object motion detection. A novel contour tracing algorithm, namely the RW （roller wheel） method, is proposed in the next section. Edge information detected by the forgoing model can be fully used by this algorithm, while the interior details will be skipped. This algorithm works in a similar way that human vision system works. Experimental results are given in the end.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2005年第8期723-727,共5页
Geomatics and Information Science of Wuhan University
基金
国家高技术研究发展计划资助项目(863-511-930-009)。
关键词
运动检测
轮廓追踪
时间差分
颜色矩
滚轮算法
motion detection
contour tracing
temporal differencing
color moments
roller wheel algorithm
