基于场景知识的移动目标检测

Abstract

Abstract:

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.

Key words: moving object detection, scene knowledge extraction, feature description, mean shift algorithm

CLC Number:

TP391

SHI Dong-cheng, YAN Li. Moving object detection based on scene knowledge[J].吉林大学学报(工学版), 2013, 43(增刊1): 275-278.

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