Distributed Image Processing for Automated Lecture Capture Post-Production

This paper describes a low-cost distributed computing approach for the post-processing of videos. It has been implemented to support the creation of composite videos from various video sources, and supports image manipulation on individual frames of the video. The principle deployment scenario for this work has been to support the automatic creation of output video based on traditional face-to-face lectures. Experimental results suggest that this approach can lead to significant speedups with a reduction in operating costs by leveraging existing underutilized equipment.