Privacy-preserving People Detection Enabled by Solid State LiDAR

Detecting people in video streams involves privacy concerns since people are often unaware of being recorded. Furthermore, cameras and commodity depth sensors are prone to variances of illumination. This work proposes light detection and ranging as sensing technology for a robust and privacy preserving people detection. A people counter is implemented, which captures a coarse human shape by concatenating multiple two dimensional range scans while people pass the sensor's view. The system works under dynamic illuminated conditions and is running as an embedded node on a single core 700 MHz processing unit. An evaluation with 20 different people crossing an entrance 100 times in each direction was carried out under controlled conditions. Results show a high precision and recall of 100 percent and 99 percent respectively for counting people and determining the walking direction. Privacy is preserved since objects are represented by distance values with a low resolution of 16x16 data points.