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, keyframes content, choosing feature, etc. In this paper we introduce a new approach for this problem based on Scale-Invariant Feature Transform (SIFT) feature, a new metric and an object retrieval method. Our algorithm is built on a Content-Based Image Retrieval (CBIR) method in which the keyframe database includes keyframes detected from video database by using our shot detection method. Experiments show that the approach of our algorithm has fairly high accuracy.
The Bao, Pham; Quang Anh, Tran; Thuong Khanh, Tran; and Ngo Da Thao, Bui
"VIDEO RETRIEVAL USING HISTOGRAM AND SIFT COMBINED WITH GRAPH-BASED IMAGE SEGMENTATION,"
Information Sciences Letters: Vol. 1
, Article 4.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol1/iss2/4