A. Belbachir, M. Hofstätter, Nenad Milosevic, P. Schön
{"title":"Embedded contours extraction for high-speed scene dynamics based on a neuromorphic temporal contrast vision sensor","authors":"A. Belbachir, M. Hofstätter, Nenad Milosevic, P. Schön","doi":"10.1109/CVPRW.2008.4563153","DOIUrl":null,"url":null,"abstract":"The paper presents a compact vision system for efficient contours extraction in high-speed applications. By exploiting the ultra high temporal resolution and the sparse representation of the sensorpsilas data in reacting to scene dynamics, the system fosters efficient embedded computer vision for ultra high-speed applications. The results reported in this paper show the sensor output quality for a wide range of object velocity (5-40 m/s), and demonstrate the object data volume independence from the velocity as well as the steadiness of the object quality. The influence of object velocity on high-performance embedded computer vision is also discussed.","PeriodicalId":102206,"journal":{"name":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2008.4563153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The paper presents a compact vision system for efficient contours extraction in high-speed applications. By exploiting the ultra high temporal resolution and the sparse representation of the sensorpsilas data in reacting to scene dynamics, the system fosters efficient embedded computer vision for ultra high-speed applications. The results reported in this paper show the sensor output quality for a wide range of object velocity (5-40 m/s), and demonstrate the object data volume independence from the velocity as well as the steadiness of the object quality. The influence of object velocity on high-performance embedded computer vision is also discussed.