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Multi-level Fusion Scheme for Target Classification using Camera and Radar Sensors
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dc.contributor.author Hyun, Eugin -
dc.contributor.author Jin, Youngseok -
dc.date.accessioned 2025-08-29T15:40:11Z -
dc.date.available 2025-08-29T15:40:11Z -
dc.date.created 2017-11-06 -
dc.date.issued 2017-07-19 -
dc.identifier.isbn 1601324642 -
dc.identifier.uri https://scholar.dgist.ac.kr/handle/20.500.11750/58974 -
dc.description.abstract We propose a multi-level fusion scheme for target detection using camera and radar sensors. For the proposed scheme, the radar sensor provides the target track information of the range, velocity, angle, and track ID. This data is applied during the vision processing step as the ROI (region of interest) where the target may exist. Next, for feature-level fusion, the Doppler spectrum of the ROI is provided to the sensor-fusion-based target classifier. In the classifier, we then determine the class of the target using an image database and a Doppler pattern database. In the experimental results, we verify the proposed processing scheme using a 24 GHz FMCW transceiver with a single antenna. CSREA Press © -
dc.language English -
dc.publisher CSREA Press -
dc.relation.ispartof Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 -
dc.title Multi-level Fusion Scheme for Target Classification using Camera and Radar Sensors -
dc.type Conference Paper -
dc.identifier.scopusid 2-s2.0-85072917392 -
dc.identifier.bibliographicCitation 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017, pp.111 - 114 -
dc.citation.conferenceDate 2017-07-17 -
dc.citation.conferencePlace US -
dc.citation.conferencePlace Las Vegas -
dc.citation.endPage 114 -
dc.citation.startPage 111 -
dc.citation.title 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 -
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