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Latest revision as of 23:18, 28 January 2021
Abstract
In automotive design, the issue of safety remains a growing priority. Recently the focus has extended beyond the occupants of the vehicle and has turned towards other vulnerable road users (VRU). Simple night vision systems have already become an important safety feature in modern high end automobiles. The next generation of advanced driver assistance systems will automate the detection of VRUs, to improve safety further by not distracting the driver's attention from the road ahead, and even identifying dangerous situations where the driver may not. This paper presents a review of the state of the art image processing techniques for automatic detection and classification of VRUs in automotive far infrared imagery.
Original document
The different versions of the original document can be found in:
- https://digital-library.theiet.org/content/conferences/10.1049/cp_20080657,
- https://www.researchgate.net/profile/Martin_Glavin/publication/224384040_A_review_of_automotive_infrared_pedestrian_detection_techniques/links/00b4951c99473a79c2000000.pdf,
- https://ieeexplore.ieee.org/document/4780948,
- https://academic.microsoft.com/#/detail/2015933685
Document information
Published on 01/01/2008
Volume 2008, 2008
DOI: 10.1049/cp:20080657
Licence: CC BY-NC-SA license
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