A personalized summarization of video life-logs from an indoor multi-camera system using a fuzzy rule-based system with domain knowledge

Information summarization and retrieval are significant research topics associated with recent advancements in sensor devices, data compression and storage techniques, and high-speed internet. As a result of these advances, it is possible for people to collect huge life-logs. Video is one of the most important life information sources. This paper describes a method of summarizing video life-logs in an office environment with a multi-camera system. Previously, multi-camera systems have been used to track moving objects or to cover a wide area. This paper focuses on capturing diverse views of each office event using a multi-camera system with several cameras observing the same area. The summarization process includes camera view selection and event sequence summarization. View selection produces a single event sequence from multiple event sequences by selecting an optimal view at each time, for which domain knowledge based on the elements of the office environment and rules from questionnaire surveys have been used. Summarization creates a summary sequence from whole sequences by using a fuzzy rule-based system to approximate human decision making. The user-entered degrees of interest in objects, persons, and events are used for a personalized summarization. We confirmed experimentally that the proposed method provides promising results.