Abstract
This paper presents the results obtained by the 2WIDE_SENSE Project, an EU funded project aimed at developing a low cost camera sensor able to acquire the full spectrum from the visible bandwidth to the Short Wave InfraRed one (from 400 to 1700 nm). Two specific applications have been evaluated, both related to the automotive field: one regarding the possibility of detecting icy and wet surfaces in front of the vehicle and the other regarding the pedestrian detection capability. The former application relies on the physical fact that water shows strong electromagnetic radiation absorption capabilities in the SWIR band around 1450 nm and thus an icy or wet pavement should be seen as dark; the latter is based on the observation that the amount of radiation in the SWIR band is quite high even at night and in case of poor weather conditions. Results show that even the use of SWIR and visible spectrum seems to be a promising approach; the use in outdoor environment is not always effective.
Highlights
Increasing the road safety is an objective of mainstream importance for every political institution and great improvement capabilities are possible with development of more intelligent vehicles
We have applied a classic approach for pedestrian detection, an SVM classifier based on deformable part models [19, 20]
This paper reports about the preliminary tests done using a state-of-the-art InGaAs camera module with the OB-VSWIR 16 microlens and high-pass SWIR filters applied on the lens
Summary
Increasing the road safety is an objective of mainstream importance for every political institution and great improvement capabilities are possible with development of more intelligent vehicles. The Short Wave InfraRed (SWIR, 0.9 μm to 1.7 μm) bandwidth shows different light reflection patterns depending on the road status (see Figure 1) [12] According to this result, some solutions based on the use of custom spectrometers have been already implemented, for example, the Volvos Road eye or the Vaisala’s Road Weather Sensors family. The development of active video-based driver assistance systems to detect preemptively dangerous situations involving vulnerable road users (VRU) as pedestrians is of fundamental importance for warning the driver or automatically taking control of the vehicle (i.e., braking) and becomes valuable in case of drivers distraction or poor visibility conditions. We have applied a classic approach for pedestrian detection, an SVM classifier based on deformable part models [19, 20]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
