An Incremental Target-Adapted Strategy for Active Geometric Calibration of Projector-Camera Systems

Abstract

The calibration of a projector-camera system is an essential step toward accurate 3-D measurement and environment-aware data projection applications, such as augmented reality. In this paper we present a two-stage easy-to-deploy strategy for robust calibration of both intrinsic and extrinsic parameters of a projector. Two key components of the system are the automatic generation of projected light patterns and the incremental calibration process. Based on the incremental strategy, the calibration process first establishes a set of initial parameters, and then it upgrades these parameters incrementally using the projection and captured images of dynamically-generated calibration patterns. The scene-driven light patterns allow the system to adapt itself to the pose of the calibration target, such that the difficulty in feature detection is greatly lowered. The strategy forms a closed-loop system that performs self-correction as more and more observations become available. Compared to the conventional method, which requires a time-consuming process for the acquisition of dense pixel correspondences, the proposed method deploys a homography-based coordinate computation, allowing the calibration time to be dramatically reduced. The experimental results indicate that an improvement of 70% in reprojection errors is achievable and 95% of the calibration time can be saved.