{"title":"基于句法模式识别的基于对象的视频编码器芯片组的设计与实现","authors":"A. Martinez-Smith, S. Mathew, R. Sridhar","doi":"10.1109/ASIC.1997.617016","DOIUrl":null,"url":null,"abstract":"This paper presents the design and partial implementation of a chip set for a new object-based video coding technique. The hardware algorithm uses unsupervised learning of image contents for efficient second-generation coding of video. Computational complexity is controlled by storing a minimum feature set, upon which higher level contents are defined. Numerical results for test video sequences are given.","PeriodicalId":300310,"journal":{"name":"Proceedings. Tenth Annual IEEE International ASIC Conference and Exhibit (Cat. No.97TH8334)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and implementation of an object-based video coder chip set based on syntactic pattern recognition\",\"authors\":\"A. Martinez-Smith, S. Mathew, R. Sridhar\",\"doi\":\"10.1109/ASIC.1997.617016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the design and partial implementation of a chip set for a new object-based video coding technique. The hardware algorithm uses unsupervised learning of image contents for efficient second-generation coding of video. Computational complexity is controlled by storing a minimum feature set, upon which higher level contents are defined. Numerical results for test video sequences are given.\",\"PeriodicalId\":300310,\"journal\":{\"name\":\"Proceedings. Tenth Annual IEEE International ASIC Conference and Exhibit (Cat. No.97TH8334)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Tenth Annual IEEE International ASIC Conference and Exhibit (Cat. No.97TH8334)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASIC.1997.617016\",\"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. Tenth Annual IEEE International ASIC Conference and Exhibit (Cat. No.97TH8334)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASIC.1997.617016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and implementation of an object-based video coder chip set based on syntactic pattern recognition
This paper presents the design and partial implementation of a chip set for a new object-based video coding technique. The hardware algorithm uses unsupervised learning of image contents for efficient second-generation coding of video. Computational complexity is controlled by storing a minimum feature set, upon which higher level contents are defined. Numerical results for test video sequences are given.