Exploring video clips in a vast collection of videos is a difficult task. It is necessary to provide an efficient system for users to express the information need for sought events in that video collection. Thus, we propose to develop AVSeeker – an active video retrieval engine – to assist users in finding appropriate moments in videos with two main query types: textual descriptions and visual examples. The main characteristic of AVSeekeris that we change the retrieval engine from a passive system to an active one, which narrows the search space by gaining clues from users through an interactive relevance feedback manner. The AVSeeker is based on the LifeSeeker system from the annual Lifelog Search Challenge with the addition of an interactive relevance feedback via concept recommendation, enriched temporal concepts, and query-bysketch functionality