Summarization of Videos by Image Quality Assessment

Marcos Vinicius Mussel Cirne, Hélio Pedrini

Abstract: Video summarization plays a key role in manipulating large amounts of digital videos, making it faster to analyze their contents and aiding in the tasks of browsing, indexing and retrieval. A straightforward method for producing the summaries is by means of extraction of color features from the video frames. However, in order to automatically generate summaries as human beings would do, the way that humans perceive images must be considered, which can be done by image quality assessment (IQA) metrics. This work presents VSQUAL, a method for summarization of videos based on objective IQA metrics, which is also used for other purposes such as shot boundary detection and keyframe extraction. Results of the proposed method are compared against other approaches of the literature with a specific evaluation metric.