@article {10.3844/jcssp.2012.853.858,
article_type = {journal},
title = {Video Retrieval using Histogram and Sift Combined with Graph-based Image Segmentation},
author = {Anh, Tran Quang and Bao, Pham and Khanh, Tran Thuong and Thao, Bui Ngo Da and Tuan, Tran Anh and Nhut, Nguyen Thanh},
volume = {8},
number = {6},
year = {2012},
month = {Mar},
pages = {853-858},
doi = {10.3844/jcssp.2012.853.858},
url = {https://thescipub.com/abstract/jcssp.2012.853.858},
abstract = {Problem statement: 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 study we introduce a new approach for this problem based on Scale-Invariant Feature Transform (SIFT) feature, a new metric and an object retrieval method. Conclusion/Recommendations: 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 algorithmhas fairly high accuracy.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}