Alexandru Costache, D. Popescu, Cosmin Popa, S. Mocanu
{"title":"多摄像机视频监控","authors":"Alexandru Costache, D. Popescu, Cosmin Popa, S. Mocanu","doi":"10.1109/CSCS.2019.00096","DOIUrl":null,"url":null,"abstract":"In this paper we aim to detect and track moving persons inside a target area and to obtain statistics regarding the regions of the area with the highest pedestrian traffic. We present or approach on video data gathering, storage and analysis, aiming to deliver real-time results. We use neural networks for both pedestrian detection and pedestrian tracking, while attempting to track persons between multiple cameras as well. We present and comment our experimental results, pointing out advantages and disadvantages.","PeriodicalId":352411,"journal":{"name":"2019 22nd International Conference on Control Systems and Computer Science (CSCS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Camera Video Surveillance\",\"authors\":\"Alexandru Costache, D. Popescu, Cosmin Popa, S. Mocanu\",\"doi\":\"10.1109/CSCS.2019.00096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we aim to detect and track moving persons inside a target area and to obtain statistics regarding the regions of the area with the highest pedestrian traffic. We present or approach on video data gathering, storage and analysis, aiming to deliver real-time results. We use neural networks for both pedestrian detection and pedestrian tracking, while attempting to track persons between multiple cameras as well. We present and comment our experimental results, pointing out advantages and disadvantages.\",\"PeriodicalId\":352411,\"journal\":{\"name\":\"2019 22nd International Conference on Control Systems and Computer Science (CSCS)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 22nd International Conference on Control Systems and Computer Science (CSCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCS.2019.00096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 22nd International Conference on Control Systems and Computer Science (CSCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCS.2019.00096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we aim to detect and track moving persons inside a target area and to obtain statistics regarding the regions of the area with the highest pedestrian traffic. We present or approach on video data gathering, storage and analysis, aiming to deliver real-time results. We use neural networks for both pedestrian detection and pedestrian tracking, while attempting to track persons between multiple cameras as well. We present and comment our experimental results, pointing out advantages and disadvantages.