Video Retrieval using Histogram and Sift Combined with Graph-based Image Segmentation
Content-Based Video Retrieval (CBVR) is still an open hard problem because of the semantic gap between low-level features and high-level features, largeness of database, keyframe's content, choosing feature. In this paper, the authors introduce a new approach for this problem based on Scale-Invariant Feature Transform (SIFT) feature, a new metric and an object retrieval method. Their algorithm is built on a Content-Based Image Retrieval (CBIR) method in which the keyframe database includes keyframes detected from video database by using their shot detection method. Experiments show that the approach of their algorithm has fairly high accuracy.