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번호판 Pose-Estimation을 이용한 주정차 인식 알고리즘 개발
김황근(Hwanggeun Kim),길정환(Jeonghwan Gil),이재석(Jaeseok Lee),최소명(Somyoung Cho),이찬호(Chanho Lee),김철수(Chulsoo Kim) 한국자동차공학회 2023 한국자동차공학회 학술대회 및 전시회 Vol.2023 No.11
Accurately verifying the complete parking status of a vehicle in automated charging and automated equipment is essential. In particular, accurately determining the parking status of a vehicle before initiating tasks such as robot-assisted automatic charging is crucial for ensuring safety. In this study, we propose a parking recognition algorithm using license plate Pose-Estimation. By using the standardized size of the license plate, we accurately measure the distance between the vehicle and the camera using perspective transformation techniques. Based on this, we analyze the movement of the license plate in a specific frame set to quickly determine the parking status of the vehicle. The proposed algorithm is expected to assist in the operation of automated equipment, enhancing overall operational efficiency and safety.
Human-Pose-Estimation을 이용한 Grid 기반 보행자 위험도 인식 기술
김황근(Hwanggeun Kim),길정환(Jeonghwan Gil),이재석(Jaeseok Lee),최소명(Somyoung Cho),이찬호(Chanho Lee),김철수(Chulsoo Kim) 한국자동차공학회 2023 한국자동차공학회 학술대회 및 전시회 Vol.2023 No.11
Pedestrian risk recognition technology is one of the essential tools in automated devices such as autonomous vehicles and collaborative robots to ensure pedestrian safety. Accurately identifying the location of pedestrians using a 2D camera is crucial for this risk recognition. Traditional methods relied on simple techniques that divided the 2D image into Regions of Interest (ROIs) or determined whether an object entered a specific area. Since these methods determine the risk based on the pixel location of the pedestrian in the 2D image without calculating the actual coordinates, errors can occur due to the cameras position, angle, or detection results. In this paper, we introduce a risk recognition algorithm that offers a more accurate approach using Human-Pose-Estimation technology and Auto Calibration. Through Calibration, we correct the cameras distortion and perspective, and using Human-Pose, we calculate the actual coordinates of the pedestrian. By placing the pedestrian in a virtual grid environment, we can evaluate the accessibility to predefined risk areas.
팬터그래프 충전 방식 전기버스 Contact Bar 자동 탐색 및 위치 인식 알고리즘 개발
최소명(Somyoung Choi),김황근(Hwanggeun Kim),길정환(Jeong Hwan Gil),이재석(Jaeseok Lee),이찬호(Chanho Lee),김철수(Chulsoo Kim) 한국자동차공학회 2023 한국자동차공학회 학술대회 및 전시회 Vol.2023 No.11
This paper presents an automatic Contact Bar detection and positioning algorithm for the PentaGraph automatic charging system used in domestic bus garages. The algorithm utilizes deep learning-based image processing techniques to real-time detect Contact Bars, track the movements of the transfer-type connector, and calculate correction values. It efficiently derives correction values for five different scenarios and experimental results demonstrate the effectiveness of this algorithm in practical applications. This research is expected to enhance the accuracy and reliability of high-capacity automatic charging systems for electric buses.
주차 차량의 자세 추정을 위한 번호판 외곽선 검출 방법
최소명(Somyoung Choi),김황근(Hwanggeun Kim),길정환(Jeong Hwan Gil),이재석(Jaeseok Lee),김철수(Chulsoo Kim) 한국자동차공학회 2022 한국자동차공학회 학술대회 및 전시회 Vol.2022 No.11
This paper studies the detection of license plate outline. This study proposes the best method for detecting license plates by calculating the distance from the vehicle through pixel values of license plates detected through various methods for detecting the outline of license plates. The license plate is detected through DNN as a preprocessing process, and an accurate outline is detected based on the image. Estimating the distance and angle is a step for estimating the posture of the vehicle, and the higher the accuracy of detecting the license plate outline of the vehicle, the higher the accuracy of estimating the posture of the vehicle. In this paper, we propose the method with the highest accuracy among the various extraction methods of the outline.