Look Both Ways: Bidirectional Visual Sensing for Automatic Multi-Camera Registration

Punarjay Chakravarty, Subodh Mishra, Sushruth Nagesh, Sagar Manglani, Graham Mills, Shubham Shrivastava

Abstract:

This work describes the automatic registration of
a large network (≈ 40) of fixed, ceiling-mounted environment
cameras spread over a large area (≈ 800 m2) using a mobile
calibration robot equipped with a single upward-facing fisheye
camera and a backlit ArUco marker for easy detection. The
fisheye camera is used to do visual odometry (VO), and the
ArUco marker facilitates easy detection of the calibration robot
in the environment cameras. In addition, the fisheye camera is
also able to detect the environment cameras. This two-way,
bidirectional detection constrains the pose of the environment
cameras to solve an optimization problem. Such an approach
can be used to automatically register a large-scale multi-camera
system used for surveillance, automated parking, or robotic
applications. This VO based multi-camera registration method
has been extensively validated using real-world experiments,
and also compared against a similar approach which uses a
LiDAR - an expensive, heavier and power hungry sensor.