Ricardo Maroquio Bernardo, L. C. Batista da Silva, P. F. Ferreira Rosa
{"title":"用于低成本小型RPAS监控应用的机载视频稳定","authors":"Ricardo Maroquio Bernardo, L. C. Batista da Silva, P. F. Ferreira Rosa","doi":"10.1109/bracis.2018.00084","DOIUrl":null,"url":null,"abstract":"This paper presents digital stabilization solution for videos captured from remotely piloted aircraft systems (RPAS) in order to enable persistent surveillance tasks based on stationary aerial images, in which situation the image quality has a direct impact on the accuracy of the algorithms for detecting independently moving objects (IMOs). The proposed method uses keypoint detection from a reference frame and tracks the displacement of these keypoints in the following frames, in order to compute the geometric transformation required to promote the alignment between the frames. Experiments were conducted in simulated 3D scenes and in real scenes, comparing different algorithms available in the literature. Using an innovative method for keypoint selection improvement, the results show that the solution is feasible even when executed in a single board computer (SBC) as the Raspberry Pi 3 Model B, providing adequate output even for real time surveillance applications.","PeriodicalId":405190,"journal":{"name":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","volume":"15 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Onboard Video Stabilization for Low Cost Small RPAS Surveillance Applications\",\"authors\":\"Ricardo Maroquio Bernardo, L. C. Batista da Silva, P. F. Ferreira Rosa\",\"doi\":\"10.1109/bracis.2018.00084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents digital stabilization solution for videos captured from remotely piloted aircraft systems (RPAS) in order to enable persistent surveillance tasks based on stationary aerial images, in which situation the image quality has a direct impact on the accuracy of the algorithms for detecting independently moving objects (IMOs). The proposed method uses keypoint detection from a reference frame and tracks the displacement of these keypoints in the following frames, in order to compute the geometric transformation required to promote the alignment between the frames. Experiments were conducted in simulated 3D scenes and in real scenes, comparing different algorithms available in the literature. Using an innovative method for keypoint selection improvement, the results show that the solution is feasible even when executed in a single board computer (SBC) as the Raspberry Pi 3 Model B, providing adequate output even for real time surveillance applications.\",\"PeriodicalId\":405190,\"journal\":{\"name\":\"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)\",\"volume\":\"15 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/bracis.2018.00084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/bracis.2018.00084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Onboard Video Stabilization for Low Cost Small RPAS Surveillance Applications
This paper presents digital stabilization solution for videos captured from remotely piloted aircraft systems (RPAS) in order to enable persistent surveillance tasks based on stationary aerial images, in which situation the image quality has a direct impact on the accuracy of the algorithms for detecting independently moving objects (IMOs). The proposed method uses keypoint detection from a reference frame and tracks the displacement of these keypoints in the following frames, in order to compute the geometric transformation required to promote the alignment between the frames. Experiments were conducted in simulated 3D scenes and in real scenes, comparing different algorithms available in the literature. Using an innovative method for keypoint selection improvement, the results show that the solution is feasible even when executed in a single board computer (SBC) as the Raspberry Pi 3 Model B, providing adequate output even for real time surveillance applications.