{"title":"基于改进亲和传播的视频拷贝检测","authors":"Peng Li, Shengxiang Gao","doi":"10.1109/ICCSN.2015.7296176","DOIUrl":null,"url":null,"abstract":"To solve the problems in the traditional BoVW (bag of visual words) method based on the K-means clustering algorithm such as bad searching precision and low time efficiency. An improved BoVW making method based on Affinity Propagation (AP) and applying for large scale dataset is proposed. E2LSH is used to match the similar video frame and vote to completing the video copy detection, and an LAP method is introduced to make the BoVW scalable. Experimental results show that the accuracy of the proposed method is substantially improved compared to the traditional methods. Besides, it also adapts large scale datasets well.","PeriodicalId":319517,"journal":{"name":"2015 IEEE International Conference on Communication Software and Networks (ICCSN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Video copy detection based on improved affinity propagation\",\"authors\":\"Peng Li, Shengxiang Gao\",\"doi\":\"10.1109/ICCSN.2015.7296176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problems in the traditional BoVW (bag of visual words) method based on the K-means clustering algorithm such as bad searching precision and low time efficiency. An improved BoVW making method based on Affinity Propagation (AP) and applying for large scale dataset is proposed. E2LSH is used to match the similar video frame and vote to completing the video copy detection, and an LAP method is introduced to make the BoVW scalable. Experimental results show that the accuracy of the proposed method is substantially improved compared to the traditional methods. Besides, it also adapts large scale datasets well.\",\"PeriodicalId\":319517,\"journal\":{\"name\":\"2015 IEEE International Conference on Communication Software and Networks (ICCSN)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Communication Software and Networks (ICCSN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSN.2015.7296176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Communication Software and Networks (ICCSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2015.7296176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
为了解决基于k均值聚类算法的传统BoVW (bag of visual words)方法中搜索精度差、时间效率低等问题。提出了一种适用于大规模数据集的基于关联传播(Affinity Propagation, AP)的改进BoVW生成方法。采用E2LSH对相似视频帧进行匹配并投票完成视频复制检测,并引入LAP方法使BoVW具有可扩展性。实验结果表明,与传统方法相比,该方法的精度有了很大提高。此外,它还能很好地适应大规模数据集。
Video copy detection based on improved affinity propagation
To solve the problems in the traditional BoVW (bag of visual words) method based on the K-means clustering algorithm such as bad searching precision and low time efficiency. An improved BoVW making method based on Affinity Propagation (AP) and applying for large scale dataset is proposed. E2LSH is used to match the similar video frame and vote to completing the video copy detection, and an LAP method is introduced to make the BoVW scalable. Experimental results show that the accuracy of the proposed method is substantially improved compared to the traditional methods. Besides, it also adapts large scale datasets well.