Video Retrieval using Histogram and Sift Combined with Graph-based Image Segmentation | Science Publications

Journal of Computer Science

Tran Anh Tuan¹  Tran Quang Anh¹  Bui Ngo Da Thao¹  Tran Thuong Khanh¹  Nguyen Thanh Nhut¹  Pham Bao¹ 

关键词: Content-Based Video Retrieval (CBVR);    Content-Based Image Retrieval (CBIR);    Scale-Invariant Feature Transform (SIFT);    natural important problem;    various properties;   

DOI  :  10.3844/jcssp.2012.853.858

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

Unknown