{"title":"使用ORB从板球广播中自动生成高光","authors":"D. Ringis, A. Pooransingh","doi":"10.1109/PACRIM.2015.7334809","DOIUrl":null,"url":null,"abstract":"This paper investigates the use of the Oriented Fast, Rotated Brief (ORB) method to automatically detect the most significant broadcast view associated with cricket broadcasts: the Bowler Run-up Sequence (BRS) for cricket highlight generation. This method is computationally less expensive than other methods proposed for BRS detection. It is shown here that only a single frame is required for training to produce acceptable results as compared to other BRS detection methods. The ORB method produced a BRS detection rate of 98.26% and false detection rate of 5.70% and average matching time of 0.059 seconds. The fast training and matching makes this ideal for real time generation of highlight sand the detection is robust to sequences with high camera motion.","PeriodicalId":350052,"journal":{"name":"2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Automated highlight generation from cricket broadcasts using ORB\",\"authors\":\"D. Ringis, A. Pooransingh\",\"doi\":\"10.1109/PACRIM.2015.7334809\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the use of the Oriented Fast, Rotated Brief (ORB) method to automatically detect the most significant broadcast view associated with cricket broadcasts: the Bowler Run-up Sequence (BRS) for cricket highlight generation. This method is computationally less expensive than other methods proposed for BRS detection. It is shown here that only a single frame is required for training to produce acceptable results as compared to other BRS detection methods. The ORB method produced a BRS detection rate of 98.26% and false detection rate of 5.70% and average matching time of 0.059 seconds. The fast training and matching makes this ideal for real time generation of highlight sand the detection is robust to sequences with high camera motion.\",\"PeriodicalId\":350052,\"journal\":{\"name\":\"2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACRIM.2015.7334809\",\"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 Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM.2015.7334809","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated highlight generation from cricket broadcasts using ORB
This paper investigates the use of the Oriented Fast, Rotated Brief (ORB) method to automatically detect the most significant broadcast view associated with cricket broadcasts: the Bowler Run-up Sequence (BRS) for cricket highlight generation. This method is computationally less expensive than other methods proposed for BRS detection. It is shown here that only a single frame is required for training to produce acceptable results as compared to other BRS detection methods. The ORB method produced a BRS detection rate of 98.26% and false detection rate of 5.70% and average matching time of 0.059 seconds. The fast training and matching makes this ideal for real time generation of highlight sand the detection is robust to sequences with high camera motion.