{"title":"Fast detection of moving object based on improved frame-difference method","authors":"Ming Zhu, Hongbo Wang","doi":"10.1109/ICCSNT.2017.8343706","DOIUrl":null,"url":null,"abstract":"It is difficult to detect the moving object in the video which is captured with the moving camera, and it costs a lot of time to use current method of object detection, because there is a large false rate based on the basic method of moving object detection. In this paper, we propose an improved frame-difference method, which can shorten the running time and improve the accuracy of the object detection. The results of the experiment show that after adding the improved frame-difference method, the detection speed is increased by 21.06 times, the image detection accuracy is improved about 8%. The algorithm is robust and it can be adapted to different scenes including indoor and outdoor. It could be applied to the field of artificial intelligence, such as Intelligent Driving, UAV aerial detection technology and so on.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSNT.2017.8343706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
It is difficult to detect the moving object in the video which is captured with the moving camera, and it costs a lot of time to use current method of object detection, because there is a large false rate based on the basic method of moving object detection. In this paper, we propose an improved frame-difference method, which can shorten the running time and improve the accuracy of the object detection. The results of the experiment show that after adding the improved frame-difference method, the detection speed is increased by 21.06 times, the image detection accuracy is improved about 8%. The algorithm is robust and it can be adapted to different scenes including indoor and outdoor. It could be applied to the field of artificial intelligence, such as Intelligent Driving, UAV aerial detection technology and so on.