{"title":"快速多运动视频分割","authors":"Dong Xu, Xuelong Li","doi":"10.1109/ICNNSP.2003.1281214","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel fast scheme to deal with multiple motion video, which contains more than one different motion objects. Change detection methods are employed under some essential prior knowledge, and the computing complexity is low. Experimental results show that the presented algorithm performs well for the multiple motion video, efficiently and effectively.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fast multiple motion video segmentation\",\"authors\":\"Dong Xu, Xuelong Li\",\"doi\":\"10.1109/ICNNSP.2003.1281214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel fast scheme to deal with multiple motion video, which contains more than one different motion objects. Change detection methods are employed under some essential prior knowledge, and the computing complexity is low. Experimental results show that the presented algorithm performs well for the multiple motion video, efficiently and effectively.\",\"PeriodicalId\":336216,\"journal\":{\"name\":\"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNNSP.2003.1281214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNNSP.2003.1281214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper proposes a novel fast scheme to deal with multiple motion video, which contains more than one different motion objects. Change detection methods are employed under some essential prior knowledge, and the computing complexity is low. Experimental results show that the presented algorithm performs well for the multiple motion video, efficiently and effectively.