S. Srigrarom, Niven Jun Liang Sie, Huimin Cheng, Kim Hoe Chew, Mengda Lee, P. Ratsamee
{"title":"基于轨迹再识别的多摄像头多无人机检测、跟踪与定位","authors":"S. Srigrarom, Niven Jun Liang Sie, Huimin Cheng, Kim Hoe Chew, Mengda Lee, P. Ratsamee","doi":"10.1109/ICA-SYMP50206.2021.9358454","DOIUrl":null,"url":null,"abstract":"This paper presents a real-time multiple camera system for detecting, tracking and localizing multiple moving drones simultaneously in a 3 dimension space. The distinct feature of the system is in its target re-identification process, which provides for information fusion among cameras based on the targets' trajectories and relative locations. Drones are detected by the multiple camera system based on motion-based blob detection, and the 2D locations of each drone in individual camera frames are tracked by A geometry- and camera-based model. From the paths of the tracked drones, their trajectories are examined using drone track feature variable. Cross-correlated among cameras for object re-identifications will allow the individual 2D position information to be integrated into overall global 3D positions of all the tracked drones from all cameras. Preliminary outdoor flight demonstrations with 2 drones flying in formation and using 3 cameras show optimal results. The system is able to detect, track, localize and re-identifying individual drone with average positional error of 8%.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification\",\"authors\":\"S. Srigrarom, Niven Jun Liang Sie, Huimin Cheng, Kim Hoe Chew, Mengda Lee, P. Ratsamee\",\"doi\":\"10.1109/ICA-SYMP50206.2021.9358454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a real-time multiple camera system for detecting, tracking and localizing multiple moving drones simultaneously in a 3 dimension space. The distinct feature of the system is in its target re-identification process, which provides for information fusion among cameras based on the targets' trajectories and relative locations. Drones are detected by the multiple camera system based on motion-based blob detection, and the 2D locations of each drone in individual camera frames are tracked by A geometry- and camera-based model. From the paths of the tracked drones, their trajectories are examined using drone track feature variable. Cross-correlated among cameras for object re-identifications will allow the individual 2D position information to be integrated into overall global 3D positions of all the tracked drones from all cameras. Preliminary outdoor flight demonstrations with 2 drones flying in formation and using 3 cameras show optimal results. The system is able to detect, track, localize and re-identifying individual drone with average positional error of 8%.\",\"PeriodicalId\":147047,\"journal\":{\"name\":\"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICA-SYMP50206.2021.9358454\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification
This paper presents a real-time multiple camera system for detecting, tracking and localizing multiple moving drones simultaneously in a 3 dimension space. The distinct feature of the system is in its target re-identification process, which provides for information fusion among cameras based on the targets' trajectories and relative locations. Drones are detected by the multiple camera system based on motion-based blob detection, and the 2D locations of each drone in individual camera frames are tracked by A geometry- and camera-based model. From the paths of the tracked drones, their trajectories are examined using drone track feature variable. Cross-correlated among cameras for object re-identifications will allow the individual 2D position information to be integrated into overall global 3D positions of all the tracked drones from all cameras. Preliminary outdoor flight demonstrations with 2 drones flying in formation and using 3 cameras show optimal results. The system is able to detect, track, localize and re-identifying individual drone with average positional error of 8%.