A Video Retrieval Algorithm Based on Spatio-temporal Feature Curves and Key Frames

Abstract

Present video retrieval methods have many problems. To solve these problems, a new video retrieval algorithm base on the combination of video spatio-temporal feature curves and key frames is proposed in this paper. In this new algorithm, the feature curves are extracted from the video, and then two videos' feature curves are compared to determine whether they have the same content or not. In the comparing process, to solve the problems of brightness offset in all frames and abrupt intense disturbance, the paper uses Grads comparison method and Exception Factor. To improve retrieval precision for videos like films, a method based on clips and key frames is added after spatio-temporal feature curves based retrieval. The new algorithm can largely reduce the data amount of video retrieval. Experimental results show the effectiveness and robustness of the algorithm.

Video Indexing and Retrieval based on Key Frame Extraction

“…O'Connor et al [7] apply a few video indexing tools, including shot segmentation, key frames selection, shots clustering, and news story segmentation, to automatically index video data for succedent misalignment browsing. Chen et al [8] propose a novel multimedia retrieval approach based on key frames of videos. This method compares video spatial-temporal feature curves to determine the similarity between the query video and the videos that the user wants to search.…”