DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Taeyeon | ko |
dc.contributor.author | Wee, Inhwan | ko |
dc.contributor.author | Shim, David Hyunchul | ko |
dc.date.accessioned | 2020-01-21T03:20:46Z | - |
dc.date.available | 2020-01-21T03:20:46Z | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.issued | 2019-10-15 | - |
dc.identifier.citation | 19th International Conference on Control, Automation and Systems (ICCAS), pp.1627 - 1631 | - |
dc.identifier.issn | 2093-7121 | - |
dc.identifier.uri | http://hdl.handle.net/10203/271638 | - |
dc.description.abstract | This paper presents a vision-based tracking algorithm for real-time drone. This method consists of cnn based object detection and object tracking using the result of detector. The detector outputs a class label and a binary mask of the object. The tracker uses this binary mask to extract object features from the background. We use this information to estimate the accurate target location and tracking the target to each frame considering the similarity between target and each detected object feature vector. We validate this method using real-time drone. | - |
dc.language | English | - |
dc.publisher | Institute of Control, Robotics and Systems | - |
dc.title | Occlusion Robust Object Detection and Tracking on a Real-time Drone | - |
dc.type | Conference | - |
dc.identifier.wosid | 000555707100241 | - |
dc.identifier.scopusid | 2-s2.0-85079104572 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 1627 | - |
dc.citation.endingpage | 1631 | - |
dc.citation.publicationname | 19th International Conference on Control, Automation and Systems (ICCAS) | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | ICC Jeju | - |
dc.identifier.doi | 10.23919/ICCAS47443.2019.8971546 | - |
dc.contributor.localauthor | Shim, David Hyunchul | - |
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