Particle Filter Based Robust Multi-Human 3D Pose Estimation for Vehicle Safety Control

Joonsang Park; Hyungwook Park

doi:10.22680/kasa2022.14.3.071

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2022 Vol.14, Issue 3 Preview Page Next Page

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

30 September 2022. pp. 71-76

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Abstract

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.

Keywords

Human Pose Estimation

Sensor Fusion

Convolutional Neural Network

Driver Monitoring System

키워드

인체 자세 추정

센서 융합

합성곱 신경망

운전자 모니터링 시스템

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Information

Publisher :Korean Auto-vehicle Safety Association
Publisher(Ko) :한국자동차모빌리티안전학회
Journal Title :Journal of Auto-vehicle Safety Association
Journal Title(Ko) :자동차안전학회지
Volume : 14
No :3
Pages :71-76
Received Date : 2022-05-27
Revised Date : 2022-07-28
Accepted Date : 2022-08-25
DOI :https://doi.org/10.22680/kasa2022.14.3.071

Journal of Auto-vehicle Safety Association ISSN:2005-9396(Print) 자동차안전학회지

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