Active Vision with Dynamic Camera Clusters
DC-VINS: Dynamic Camera Visual Inertial Navigation System with Online Calibration
Jason Rebello, Chunshang Li and Steven L. Waslander.
ICCV Workshop, 2021]
we present the online extrinsic calibration between a dynamic camera mounted to an actuated mechanism and an IMU mounted to the body of the vehicle integrated into a Visual Odometry pipeline. In addition, we provide a degeneracy analysis of the calibration parameters leading to a novel parameterization of the actuated mechanism used in the calibration. We build our calibration into the VINS-Fusion package and show that we are able to accurately recover the calibration parameters online while manipulating the viewpoint of the camera to feature rich areas
AC/DCC: Accurate Calibration of Dynamic Camera Clusters for Visual SLAM
Jason Rebello, Augus Fung and Steven L. Waslander.
A novel method that performs accurate calibration of a Dynamic Camera Cluster with multiple static cameras using a pose-loop error formulation. We also present an analysis of the degenerate parameters in the calibration when the joint angle value are not available.
Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters
Christopher L. Choi, Jason Rebello, Leonid Koppel, Pranav Ganti, Arun Das, and Steven L. Waslander.
Calibration of a DCC was performed without knowledge of joint encoder angles and tested in a Visual Intertial Odometry application.
Autonomous Active Calibration of a Dynamic Camera Cluster using Next-Best-View
Jason Rebello, Arun Das and Steven L. Waslander.
A novel active vision approach to DCC calibration, which directly reduces parameter uncertainty by selecting calibration measurements using an information theoretic next-best-view policy was developed.
Calibration of a Dynamic Camera Cluster for Multi-Camera Visual SLAM
Arun Das and Steven L. Waslander
A calibration method for dynamic multi-camera clusters, where one or more of the cameras is mounted to an actuated mechanism such as a gimbal or robotic manipulator.