Controlling camera and lights for intelligent image acquisition and merging

Abstract

Docking craft in space and guiding mining machines are areas that often use remote video cameras equipped with one or more controllable light sources. In these applications, the problem of parameter selection arises: how to choose the best parameters for the camera and lights? Another problem is that a single image often cannot capture the whole scene properly and a composite image needs to be rendered. In this paper, we report on our progress with the CITO Lights and Camera project that addresses the parameter selection and merging problems for such systems. The prototype knowledge-based controller adjusts lighting to iteratively acquire a collection of images of a target. At every stage, an entropy-based merging module combines these images to produce a composite. The result is a final composite image that is optimized for further image processing tasks, such as pose estimation or tracking.