DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, S.-H. | ko |
dc.contributor.author | Choi, Han-Lim | ko |
dc.date.accessioned | 2018-07-24T02:26:49Z | - |
dc.date.available | 2018-07-24T02:26:49Z | - |
dc.date.created | 2018-07-02 | - |
dc.date.created | 2018-07-02 | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Journal of Institute of Control, Robotics and Systems, v.23, no.3, pp.157 - 164 | - |
dc.identifier.issn | 1976-5622 | - |
dc.identifier.uri | http://hdl.handle.net/10203/244102 | - |
dc.description.abstract | This paper considers vision-based multiple moving target-tracking and target-type recognition methods for unmanned airborne surveillance systems. The detection of moving objects and target-type recognition in a moving image frame are the essential parts of airborne surveillance systems. We propose an optical flow-based object detection method with image stabilization functions to detect moving objects in a moving image frame, and a combination of the Support Vector Machine (SVM) with Convolutional Neural Networks (CNNs) model for the target-type recognition. The experiment of an airborne surveillance scenario using a quadcopter with a camera is conducted to demonstrate the performance of the proposed method. © ICROS 2017. | - |
dc.language | Korean | - |
dc.publisher | Institute of Control, Robotics and Systems | - |
dc.subject | Clutter (information theory) | - |
dc.subject | Convolution | - |
dc.subject | Image processing | - |
dc.subject | Monitoring | - |
dc.subject | Neural networks | - |
dc.subject | Object detection | - |
dc.subject | Optical flows | - |
dc.subject | Security systems | - |
dc.subject | Stabilization | - |
dc.subject | Support vector machines | - |
dc.subject | Tracking (position) | - |
dc.subject | Airborne Surveillance | - |
dc.subject | Convolutional neural network | - |
dc.subject | Detection of moving object | - |
dc.subject | Image stabilization | - |
dc.subject | Moving target tracking | - |
dc.subject | Quadcopter | - |
dc.subject | SVM(support vector machine) | - |
dc.subject | Target type | - |
dc.subject | Target tracking | - |
dc.title | Moving target tracking and recognition method for unmanned airborne surveillance systems | - |
dc.type | Article | - |
dc.identifier.scopusid | 2-s2.0-85014658311 | - |
dc.type.rims | ART | - |
dc.citation.volume | 23 | - |
dc.citation.issue | 3 | - |
dc.citation.beginningpage | 157 | - |
dc.citation.endingpage | 164 | - |
dc.citation.publicationname | Journal of Institute of Control, Robotics and Systems | - |
dc.identifier.doi | 10.5302/J.ICROS.2017.16.0200 | - |
dc.contributor.localauthor | Choi, Han-Lim | - |
dc.contributor.nonIdAuthor | Kim, S.-H. | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Airborne surveillance | - |
dc.subject.keywordAuthor | CNNs (Convolutional Neural Networks) | - |
dc.subject.keywordAuthor | Detection of moving object | - |
dc.subject.keywordAuthor | Image stabilization | - |
dc.subject.keywordAuthor | Multiple moving target-tracking | - |
dc.subject.keywordAuthor | Optical flow | - |
dc.subject.keywordAuthor | Quadcopter | - |
dc.subject.keywordAuthor | SVM (Support Vector Machine) | - |
dc.subject.keywordAuthor | Target-type recognition | - |
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