The camera using panoramic annular lens (PAL) can capture the surrounding scene in a view of 360° without any
scanning component. Due to severe distortions, the image formed by PAL must be unwrapped into a perspective-view
image in order to get consistency with the human's visual custom. However the unfilled pixels would probably exist
after unwrapping as a result of the non-uniform resolution in the PAL image, hence the interpolation should be employed
in the phase of the forward projection unwrapping. We also evaluated the performance of several interpolation
techniques for unwrapping the PAL image on a series of frequency-patterned images as a simulation by using three
image quality indexes: MSE, SSIM and S-CIELAB. The experiment result revealed that those interpolation methods had
better capability for the low frequent PAL images. The Bicubic, Ferguson and Newton interpolations performed
relatively better at higher frequencies, while Bilinear and Bezier could achieve better result at lower frequency. Besides,
the Nearest method had poorest performance in general and the Ferguson interpolation was excellent in both high and
low frequencies.
In this paper, we proposed a video analysis system in a vehicle using Panoramic Angular Lens (PAL) camera. The
system consists two parts: one is using a PAL camera which is installed on the top of the vehicle to obtain obstacle
position and compute the distance from the vehicle; the other is to configure a PAL camera inside the vehicle, which can
provide the driver's face pose and eye status information as well as the driver's viewing scene, then several image
algorithm are applied to analyze the status of driver and detect the object in front of the vehicle. Our contribution is that
the large field view of PAL camera is well used in the application of Intelligent Transportation System, and to research
the vehicle and driver information at the same time with a single panoramic camera. Meanwhile the system was very
simple.
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