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Vehicle Orientation Detection Using CNNVehicle Orientation Detection Using CNN
- Other Titles
- Vehicle Orientation Detection Using CNN
- Authors
- Nguyen Huu Thang; 김재민
- Issue Date
- 2021
- Publisher
- 한국전기전자학회
- Keywords
- Vehicle Orientation; Vehicle Detection; Real-Time; Convolutional Neural Network(CNN)
- Citation
- 전기전자학회논문지, v.25, no.4, pp.619 - 624
- Journal Title
- 전기전자학회논문지
- Volume
- 25
- Number
- 4
- Start Page
- 619
- End Page
- 624
- ISSN
- 1226-7244
- Abstract
- Vehicle orientation detection is a challenging task because the orientations of vehicles can vary in a wide rangein captured images. The existing methods for oriented vehicle detection require too much computation time to beapplied to a real-time system. We propose Rotate YOLO, which has a set of anchor boxes with multiple scales,ratios, and angles to predict bounding boxes. For estimating the orientation angle, we applied angle-related IoUwith CIoU loss to solve the underivable problem from the calculation of SkewIoU. Evaluation results on threepublic datasets DLR Munich, VEDAI and UCAS-AOD demonstrate the efficiency of our approach
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Related Researcher
- Kim, Jae min
- Engineering (Electronic & Electrical Engineering)