{"title":"轻量级可搜索的屏幕视频记录","authors":"Mattias Marder, A. Geva, Yaoping Ruan","doi":"10.1109/VCIP.2012.6410783","DOIUrl":null,"url":null,"abstract":"Command logging of maintenance and operation activities of modern computer systems has become an integral component of customer and audit requirements. In recent years, this logging has usually been achieved via desktop video recording. However, the conventional approach of video recording requires high computation overhead, high network bandwidth, and a large storage size. Searching through video files is also a challenge. In this paper, we present a lossy, but text text-preserving, compression scheme that meets these challenges by creating a sparse bitonal image suitable for optical character recognition (OCR). Using our system for auditing, the bitonal image gets stored on a server. Due to the mechanism's text-preserving compression, we can apply OCR off-line to create annotations of each video frame, making the output searchable. Compared to state-of-the-art compression of raw video, our approach can reduce file size by 50-80%, while using CPU and memory resources similar to other methods.","PeriodicalId":103073,"journal":{"name":"2012 Visual Communications and Image Processing","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Lightweight searchable screen video recording\",\"authors\":\"Mattias Marder, A. Geva, Yaoping Ruan\",\"doi\":\"10.1109/VCIP.2012.6410783\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Command logging of maintenance and operation activities of modern computer systems has become an integral component of customer and audit requirements. In recent years, this logging has usually been achieved via desktop video recording. However, the conventional approach of video recording requires high computation overhead, high network bandwidth, and a large storage size. Searching through video files is also a challenge. In this paper, we present a lossy, but text text-preserving, compression scheme that meets these challenges by creating a sparse bitonal image suitable for optical character recognition (OCR). Using our system for auditing, the bitonal image gets stored on a server. Due to the mechanism's text-preserving compression, we can apply OCR off-line to create annotations of each video frame, making the output searchable. Compared to state-of-the-art compression of raw video, our approach can reduce file size by 50-80%, while using CPU and memory resources similar to other methods.\",\"PeriodicalId\":103073,\"journal\":{\"name\":\"2012 Visual Communications and Image Processing\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Visual Communications and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP.2012.6410783\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Visual Communications and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP.2012.6410783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Command logging of maintenance and operation activities of modern computer systems has become an integral component of customer and audit requirements. In recent years, this logging has usually been achieved via desktop video recording. However, the conventional approach of video recording requires high computation overhead, high network bandwidth, and a large storage size. Searching through video files is also a challenge. In this paper, we present a lossy, but text text-preserving, compression scheme that meets these challenges by creating a sparse bitonal image suitable for optical character recognition (OCR). Using our system for auditing, the bitonal image gets stored on a server. Due to the mechanism's text-preserving compression, we can apply OCR off-line to create annotations of each video frame, making the output searchable. Compared to state-of-the-art compression of raw video, our approach can reduce file size by 50-80%, while using CPU and memory resources similar to other methods.