{"title":"一种新的H.264/AVC比特流场景变化检测算法","authors":"Jie Feng, Aiai Huang, Yaowu Chen","doi":"10.1109/PACIIA.2008.246","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel scene change detection algorithm in the H.264/AVC compressed domain directly. Three major statistical features are used: (i) bit allocation for intra mode macroblocks (BIM), (ii) bit allocation for inter mode macroblocks (BPM), and (iii) the number of skip mode macroblocks in a frame. These features can be easily extracted from the H.264/AVC bitstreams. Besides the percent of skip macroblocks in a frame, an adaptive threshold based on the ratio of BIM to BPM is used to determine the abrupt and the gradual scene changes respectively. Experimental results indicate that the proposed algorithm achieves the good performance with a low computational complexity.","PeriodicalId":275193,"journal":{"name":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","volume":"182 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Novel Scene Change Detection Algorithm for H.264/AVC Bitstreams\",\"authors\":\"Jie Feng, Aiai Huang, Yaowu Chen\",\"doi\":\"10.1109/PACIIA.2008.246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a novel scene change detection algorithm in the H.264/AVC compressed domain directly. Three major statistical features are used: (i) bit allocation for intra mode macroblocks (BIM), (ii) bit allocation for inter mode macroblocks (BPM), and (iii) the number of skip mode macroblocks in a frame. These features can be easily extracted from the H.264/AVC bitstreams. Besides the percent of skip macroblocks in a frame, an adaptive threshold based on the ratio of BIM to BPM is used to determine the abrupt and the gradual scene changes respectively. Experimental results indicate that the proposed algorithm achieves the good performance with a low computational complexity.\",\"PeriodicalId\":275193,\"journal\":{\"name\":\"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application\",\"volume\":\"182 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACIIA.2008.246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIIA.2008.246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Scene Change Detection Algorithm for H.264/AVC Bitstreams
In this paper, we present a novel scene change detection algorithm in the H.264/AVC compressed domain directly. Three major statistical features are used: (i) bit allocation for intra mode macroblocks (BIM), (ii) bit allocation for inter mode macroblocks (BPM), and (iii) the number of skip mode macroblocks in a frame. These features can be easily extracted from the H.264/AVC bitstreams. Besides the percent of skip macroblocks in a frame, an adaptive threshold based on the ratio of BIM to BPM is used to determine the abrupt and the gradual scene changes respectively. Experimental results indicate that the proposed algorithm achieves the good performance with a low computational complexity.