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Particle Filter Based Robust Multi-Human 3D Pose Estimation for Vehicle Safety Control
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차량 안전 제어를 위한 파티클 필터 기반의 강건한 다중 인체 3차원 자세 추정

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Type
Academic journal
Author
Joonsang Park (현대자동차) Hyungwook Park (현대자동차)
Journal
한국자동차안전학회 Journal Of Auto-Vehicle Safety Association Vol.14 No.3 KCI Accredited Journals
Published
2022.9
Pages
71 - 76 (6page)

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Particle Filter Based Robust Multi-Human 3D Pose Estimation for Vehicle Safety Control
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In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.
#Human Pose Estimation(인체 자세 추정) #Sensor Fusion(센서 융합) #Convolutional Neural Network(합성곱 신경망) #Driver Monitoring System(운전자 모니터링 시스템)

Contents

ABSTRACT
1. 서론
2. 키포인트 추출 및 승객 매칭
3. 파티클 필터 활용 상태 추정
4. 실험
5. 결론
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