Automatic Quality Analysis for Film and Video Restoration
A considerable amount of work in larger film and video restoration projects is dedicated to manually exploring the audiovisual content in order to estimate the costs for restoration and to plan the restoration. Manual exploration is a significant cost factor. In this paper we propose automatic content analysis algorithms and summarization techniques which allow the reduction of manual inspection time in a software based restoration environment. The throughput requirement for analysis of dust and other defects is reached by sparse application of the detectors in the image sequence while retaining sufficient detection accuracy. Analysis result metadata are represented in a MPEG-7 standard compliant way. The proposed defect summary visualization tools facilitate efficient exploration of visually impaired content by the user.