| 제목 |
기계학습 기반 객체 분류를 통한 특징 지도 작성 |
| 분야 |
ITS/차량 소프트웨어 |
| 언어 |
Korean |
| 저자 |
강동완(국민대학교), 김명준(국민대학교), 선화동(현대엠엔소프트), 김정하(국민대학교) |
| Key Words |
Feature map(특징지도), Mapping(지도작성), Classification(분류), Clustering(군집화), Pointcloud(점 군집), SVM(서포트벡터머신), DBSCAN(디비스캔), Euclidean clustering(유클리디안 클러스터링), LiDAR(라이다), Unmanned vehicles(무인 자동차) |
| 초록 |
Unmanned vehicles require environmental awareness when moving from origin to destination, as well as a high semantic knowledge of the environment. This study deals with the removal of noise from point cloud maps used in the environmental recognition systems of unmanned vehicles. However, a moving object is unnecessary on a map. In this study, we define noise as unnecessary and we deal with noise removal systems. This study proposes to define the region of interest based on the driving line of an unmanned vehicle, object separation using local thresholds, improved clustering using Euclidean clustering and DBSCAN, and classification using the support vector machine(SVM). This method allows for the classification of solid lines, dotted lines, median strips, guardrails, and noise. |
| 원문(PDF) |
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