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Digital video content is appearing in many new applications. There is a need for efficient video indexing, quick browsing, and easy retrieval of video content of interest in video clips. In this thesis, we analyze video structure and use a hierarchical summarization strategy to get a multilevel video summary. Keyframes from video are extracted from each video shot by comparing the similarity between frames. Using an affinity matrix which lists the similarities of every pairs of keyframes, similar keyframes are clustered and adjacent shots within a specified distance are merged into groups. These groups are organized into scenes that are independent story units. From scenes representative frames are selected to construct a hierarchy summary.