Video Summarization using Hierarchical Shot Boundary Detection Approach

Video summarization and retrieval plays a vital role in video management systems involving modules such as shot boundary detection, key frame extraction and feature representation. Among these modules, shot boundary detection (SBD) is the important primary step, over which the entire retrieval performance relies on. In this paper, a new hierarchical shot boundary detection mechanism is proposed to alleviate the redundant key frames in video summarization. Initially, the abrupt transitions in the videos are detected using Weber Local Descriptor (WLD) and primary key frames are extracted. After primary key frame extraction, Fourier Transform (FT) which is complementary to WLD is used to prune the redundant key frames on the highly challenging videos with varying lighting effects, object and camera motion. The proposed hierarchical SBD algorithm is evaluated on three datasets viz. TRECVID, OPEN VIDEO. The validation of the proposed algorithm on these dataset yields promising results in terms of precision, recall, F-score, and Compression rate.