{"title":"实验室小动物跟踪的一个应用CUDA技术进行计算机视觉算法的优化","authors":"D. Duque","doi":"10.1109/SeGAH.2018.8401380","DOIUrl":null,"url":null,"abstract":"This article describes a system that aims to track small animals in the context of laboratory tests in all lighting conditions. The proposed system consists of a 3D sensor and a GPU accelerated computing unit, equipped with CUDA (Compute Unified Device Architecture) technology. The data acquired by the 3D sensor, i.e. the camera, is processed by an algorithm that uses parallelization techniques to detect small animals in real time. To assess the benefits of such parallelism, it was compared with a non-parallel algorithm. Although the research is still at an early stage, the preliminary results demonstrate that the proposed method has potential to be applied in a laboratory environment.","PeriodicalId":299252,"journal":{"name":"2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tracking of small animals in laboratory An application of CUDA technology for the optimization of computer vision algorithms\",\"authors\":\"D. Duque\",\"doi\":\"10.1109/SeGAH.2018.8401380\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article describes a system that aims to track small animals in the context of laboratory tests in all lighting conditions. The proposed system consists of a 3D sensor and a GPU accelerated computing unit, equipped with CUDA (Compute Unified Device Architecture) technology. The data acquired by the 3D sensor, i.e. the camera, is processed by an algorithm that uses parallelization techniques to detect small animals in real time. To assess the benefits of such parallelism, it was compared with a non-parallel algorithm. Although the research is still at an early stage, the preliminary results demonstrate that the proposed method has potential to be applied in a laboratory environment.\",\"PeriodicalId\":299252,\"journal\":{\"name\":\"2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SeGAH.2018.8401380\",\"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 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SeGAH.2018.8401380","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tracking of small animals in laboratory An application of CUDA technology for the optimization of computer vision algorithms
This article describes a system that aims to track small animals in the context of laboratory tests in all lighting conditions. The proposed system consists of a 3D sensor and a GPU accelerated computing unit, equipped with CUDA (Compute Unified Device Architecture) technology. The data acquired by the 3D sensor, i.e. the camera, is processed by an algorithm that uses parallelization techniques to detect small animals in real time. To assess the benefits of such parallelism, it was compared with a non-parallel algorithm. Although the research is still at an early stage, the preliminary results demonstrate that the proposed method has potential to be applied in a laboratory environment.