A modification of retake detection using simple signature and LCS algorithm

Rushes videos consist of two types of content: the useless content and the redundant content (retakes). Then, automatic retake detection is more challenging due to the difficulty of eliminating repetitive takes, that are usually have different lengths and motion patterns. To overcome this challenge, previous approaches represent video segments using a longer string which is converted from SIFT matching, or a combination of different features. However, these require a large computational time and do not assist in improving a performance. In this work, we introduce a simple signature (global feature) to represent video segments because of its simplicity and effectiveness. The similarity between each pair of signature sequences was determined by using the Longest Common Subsequence algorithm (LCS). A simple retake detection was then used to detect a retake. This proposed was applied to the TRECVID BBC Rushed 2007 and 2008. The results showed that using a simple signature provides a high degree of accuracy, and reduces a computation time in feature extraction and LCS matching.