Yu Xiaoyang, Yu Yang, Yu Shuchun, Song Yang, Yang Huimin, Liu Xifeng
{"title":"一种基于改进帧差和改进高斯混合模型的运动目标检测方法","authors":"Yu Xiaoyang, Yu Yang, Yu Shuchun, Song Yang, Yang Huimin, Liu Xifeng","doi":"10.1109/MIC.2013.6757972","DOIUrl":null,"url":null,"abstract":"The existing motion detection methods include background subtraction and frame difference. But it is prone to exist some holes with frame difference method and it is difficult to build background model using background subtraction method. So the test results did not achieve the ideal state. Aim at these problem, this paper combines frame difference method improved by motion history image with background subtraction method based on improved Gaussian mixture model to detect the motion object. The experimental results show the method has achieved a satisfactory effect.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A novel motion object detection method based on improved frame difference and improved Gaussian mixture model\",\"authors\":\"Yu Xiaoyang, Yu Yang, Yu Shuchun, Song Yang, Yang Huimin, Liu Xifeng\",\"doi\":\"10.1109/MIC.2013.6757972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The existing motion detection methods include background subtraction and frame difference. But it is prone to exist some holes with frame difference method and it is difficult to build background model using background subtraction method. So the test results did not achieve the ideal state. Aim at these problem, this paper combines frame difference method improved by motion history image with background subtraction method based on improved Gaussian mixture model to detect the motion object. The experimental results show the method has achieved a satisfactory effect.\",\"PeriodicalId\":404630,\"journal\":{\"name\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MIC.2013.6757972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6757972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel motion object detection method based on improved frame difference and improved Gaussian mixture model
The existing motion detection methods include background subtraction and frame difference. But it is prone to exist some holes with frame difference method and it is difficult to build background model using background subtraction method. So the test results did not achieve the ideal state. Aim at these problem, this paper combines frame difference method improved by motion history image with background subtraction method based on improved Gaussian mixture model to detect the motion object. The experimental results show the method has achieved a satisfactory effect.