{"title":"确定人群运动模式的人群视频序列处理方法","authors":"S. Sholtanyuk, Q. Bu, A. Nedzved","doi":"10.52928/2070-1624-2024-42-1-26-33","DOIUrl":null,"url":null,"abstract":"Nowadays, homogeneous objects clusters motion is one of the most important and rapidly developing computer \nvision and machine learning application. In this paper, we consider the crowd motion patterns determination \nby using motion maps that we calculate with FlowNet, a neural network examining motion of objects in a video \nsequence. This approach allows us to get information on the crowd direction and velocity with relation to other \nobjects of scene, which plays the key role in behavior analysis and security establishment. Besides, we consider \nmethods for preliminary video sequence processing, including frame combination, to estimate motion maps more \nprecisely and improve the effectiveness of the dynamic scenes analysis.","PeriodicalId":386243,"journal":{"name":"HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CROWD VIDEO SEQUENCES PROCESSING METHODS \\nFOR DETERMINING THE CROWD MOTION PATTERNS\",\"authors\":\"S. Sholtanyuk, Q. Bu, A. Nedzved\",\"doi\":\"10.52928/2070-1624-2024-42-1-26-33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, homogeneous objects clusters motion is one of the most important and rapidly developing computer \\nvision and machine learning application. In this paper, we consider the crowd motion patterns determination \\nby using motion maps that we calculate with FlowNet, a neural network examining motion of objects in a video \\nsequence. This approach allows us to get information on the crowd direction and velocity with relation to other \\nobjects of scene, which plays the key role in behavior analysis and security establishment. Besides, we consider \\nmethods for preliminary video sequence processing, including frame combination, to estimate motion maps more \\nprecisely and improve the effectiveness of the dynamic scenes analysis.\",\"PeriodicalId\":386243,\"journal\":{\"name\":\"HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52928/2070-1624-2024-42-1-26-33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52928/2070-1624-2024-42-1-26-33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CROWD VIDEO SEQUENCES PROCESSING METHODS
FOR DETERMINING THE CROWD MOTION PATTERNS
Nowadays, homogeneous objects clusters motion is one of the most important and rapidly developing computer
vision and machine learning application. In this paper, we consider the crowd motion patterns determination
by using motion maps that we calculate with FlowNet, a neural network examining motion of objects in a video
sequence. This approach allows us to get information on the crowd direction and velocity with relation to other
objects of scene, which plays the key role in behavior analysis and security establishment. Besides, we consider
methods for preliminary video sequence processing, including frame combination, to estimate motion maps more
precisely and improve the effectiveness of the dynamic scenes analysis.