Pub Date : 2023-11-16DOI: 10.5594/JMI.2023.3321102
David Edwards;Siddhi Imming
Consumer expectation when it comes to the viewing experience is often based on watching tier 1 sports productions. In response, sports programmers are searching for solutions that deliver an engaging experience at a cost that is in line with the available budget. Artificial intelligence (AI)-driven sports production solutions have been available for some time. But to date, the ability to accurately track sporting action combined with visual clarity has been a challenge. This article describes how a panoramic camera system can be implemented to monitor the entire field of play, to feed an AI system that identifies the sporting action. Furthermore, how the AI engine can drive a high-quality pan-tilt-zoom (PTZ) camera to follow the action to deliver the program feed is also described. The article also discusses how the AI engine can accurately point the PTZ camera—taking into account video and AI processing delays, how those processing latencies can be measured, to forward-predict directional vectors and correctly point the program feed camera irrespective of distance from the camera and the variation in angular velocity realized.
{"title":"Sports Production Through AI-Powered Sports Action Tracking and PTZ Cameras","authors":"David Edwards;Siddhi Imming","doi":"10.5594/JMI.2023.3321102","DOIUrl":"https://doi.org/10.5594/JMI.2023.3321102","url":null,"abstract":"Consumer expectation when it comes to the viewing experience is often based on watching tier 1 sports productions. In response, sports programmers are searching for solutions that deliver an engaging experience at a cost that is in line with the available budget. Artificial intelligence (AI)-driven sports production solutions have been available for some time. But to date, the ability to accurately track sporting action combined with visual clarity has been a challenge. This article describes how a panoramic camera system can be implemented to monitor the entire field of play, to feed an AI system that identifies the sporting action. Furthermore, how the AI engine can drive a high-quality pan-tilt-zoom (PTZ) camera to follow the action to deliver the program feed is also described. The article also discusses how the AI engine can accurately point the PTZ camera—taking into account video and AI processing delays, how those processing latencies can be measured, to forward-predict directional vectors and correctly point the program feed camera irrespective of distance from the camera and the variation in angular velocity realized.","PeriodicalId":49512,"journal":{"name":"SMPTE Motion Imaging Journal","volume":"132 10","pages":"6-12"},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138138412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}