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Detection of Dangerous Driving Postures Based on Depth Images Using an Anchor Regression Method China Merchants Testing Vehicle Technology Research Institut

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Xu, Hailan, author.
Contributor:
Chen, Zhenming
He, Wenhao
Li, Wuhuan
Liu, Yunjie
Lu, Jun
Wang, Xin
Conference Name:
SAE 2025 Intelligent and Connected Vehicles Symposium (2025-09-19 : Shanghai, China)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2025
Summary:
Perceiving the movement characteristics of specific body parts of a driver is crucial for determining their activity. Moreover, the driver's body posture significantly impacts personnel safety during collision. This study investigates the creation of a dataset using Kinect depth camera for acquiring, organizing, annotating with skeleton tracking assistance, and optimizing interpolation. The pose recognition methods enhanced through an anchor regression mechanism, leading to the refinement of a lightweight anchor regression network capable of end-to-end learning ability from depth images. The improved backbone neck head structure offers advantages of reduced model parameters and enhanced accuracy. This engineering optimization makes it better suited for practical applications within vehicles with limited computational resources limitations and high real-time demands
Notes:
Vendor supplied data
Publisher Number:
2025-01-7343
Access Restriction:
Restricted for use by site license

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