摘要
依据背景差法中背景建模的思想,从提取场景知识的角度出发,建立待检测场景的场景知识库,从而提出一种基于场景知识的移动目标检测算法。使用改进的均值漂移算法对待检测场景进行分割,并提取分割后各个区域的底层视觉特征建立场景知识库;从新的场景帧图像中获取各区域的知识特征向量,然后根据和原场景知识库中各特征向量的匹配结果检测出移动目标信息。仿真结果表明,该方法能有效地检测出场景中原有目标和新进入场景目标的移动信息,并在一定程度上改善了目标阴影、形变等噪声对检测结果的干扰。
According to the background modeling thought in background subtraction algorithm and developed from the point of view of extracting scene knowledge to establish the scene knowledge base,an algorithm of moving object detection based on scene knowledge was proposed.In this algorithm,the features of each segmented regions were extracted to build a scene knowledge base after we used an improved mean-shift method to segment the scene image;The feature vectors from the new frame image were extracted,and the information of the moving objects were detected by matching the new feature vectors with the pre-existing feature vectors we can get from the scene knowledge base.The simulation result shows that the proposed method can detect the moving information of original object and new object in the scene effectively and is robust to the noise of shadow and the deformation of the object.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2013年第S1期275-278,共4页
Journal of Jilin University:Engineering and Technology Edition
