Roadside LiDAR Vehicle Detection and Tracking Using Range and Intensity Background Subtraction

Algorithm 2

Coarse-Fine Triangle Algorithm.

Input: Aggregated Distances for Elevation-Azimuth Angular Units
Outputs: Background vs. Foreground Thresholds
For Every Elevation and Azimuth Unit
(1)	Non-returnable points:
If non-returnable points are the majority, then consider a maximum range distance. (e.g., 200 meters) as backgrounds.
Else, remove all non-returnable points.
(2)	Coarse Step:
Use the default function to generate the histogram counts.
Find the bin edge value that contains maximum counts
Delete the points larger than , where is the standard deviation
(3)	Fine Step:
Find the maximum range value after Coarse Step
New bin_size =  /100
(4)	Create new histogram counts on [0, ] with new bin size.
(5)	Apply the Triangle Algorithm in Figure 3.
(6)	Save the threshold for this Elevation-Azimuth Angular Unit
End For