Sai Siddartha Maram, Neeraj Kumar, J. Rodrigues, S. Tanwar, Arjav Jain
{"title":"图像到信号,信号到亮点","authors":"Sai Siddartha Maram, Neeraj Kumar, J. Rodrigues, S. Tanwar, Arjav Jain","doi":"10.1109/GLOBECOM42002.2020.9347962","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a framework to generate cricket highlights from broadcasted cricket matches. Generating cricket highlights is a difficult problem, due to the duration and rules of the game. We formulate the highlight generation problem as a key-event initialization and key-event-closure identification problem. We propose an Inverse Hierarchical Framework, which is generic and capable of automatically generating highlights of a broadcasted cricket match. We introduce a novel context-aware approach for event-initialization and a Structural Similarity Index-based approach for event-closure detection. Despite the quality of highlights being a subjective measure we provide an evaluation of our framework by comparing it with official highlights on various metrics. We also perform a user-survey on the generated highlights. The approval of the users and overlap between the generated highlights and official highlights indicate the robustness of our framework.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"48 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Images to Signals, Signals to Highlights\",\"authors\":\"Sai Siddartha Maram, Neeraj Kumar, J. Rodrigues, S. Tanwar, Arjav Jain\",\"doi\":\"10.1109/GLOBECOM42002.2020.9347962\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a framework to generate cricket highlights from broadcasted cricket matches. Generating cricket highlights is a difficult problem, due to the duration and rules of the game. We formulate the highlight generation problem as a key-event initialization and key-event-closure identification problem. We propose an Inverse Hierarchical Framework, which is generic and capable of automatically generating highlights of a broadcasted cricket match. We introduce a novel context-aware approach for event-initialization and a Structural Similarity Index-based approach for event-closure detection. Despite the quality of highlights being a subjective measure we provide an evaluation of our framework by comparing it with official highlights on various metrics. We also perform a user-survey on the generated highlights. The approval of the users and overlap between the generated highlights and official highlights indicate the robustness of our framework.\",\"PeriodicalId\":12759,\"journal\":{\"name\":\"GLOBECOM 2020 - 2020 IEEE Global Communications Conference\",\"volume\":\"48 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GLOBECOM 2020 - 2020 IEEE Global Communications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOBECOM42002.2020.9347962\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOBECOM42002.2020.9347962","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a framework to generate cricket highlights from broadcasted cricket matches. Generating cricket highlights is a difficult problem, due to the duration and rules of the game. We formulate the highlight generation problem as a key-event initialization and key-event-closure identification problem. We propose an Inverse Hierarchical Framework, which is generic and capable of automatically generating highlights of a broadcasted cricket match. We introduce a novel context-aware approach for event-initialization and a Structural Similarity Index-based approach for event-closure detection. Despite the quality of highlights being a subjective measure we provide an evaluation of our framework by comparing it with official highlights on various metrics. We also perform a user-survey on the generated highlights. The approval of the users and overlap between the generated highlights and official highlights indicate the robustness of our framework.