International Journal of Computer Vision
The Truth about Corel - Evaluation in Image Retrieval
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Automatic video interpretation: a novel algorithm for temporal scenario recognition
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Online surveillance video archive system
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
MIS'05 Proceedings of the 11th international conference on Advances in Multimedia Information Systems
Appearance based retrieval for tracked objects in surveillance videos
Proceedings of the ACM International Conference on Image and Video Retrieval
Chapter 8: multimedia and multimodal information retrieval
Search Computing
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In this paper, we propose a novel query language for video indexing and retrieval that (1) enables to make queries both at the image level and at the semantic level (2) enables the users to define their own scenarios based on semantic events and (3) retrieves videos with both exact matching and similarity matching. For a query language, four main issues must be addressed: data modeling, query formulation, query parsing and query matching. In this paper we focus and give contributions on data modeling, query formulation and query matching. We are currently using color histograms and SIFT features at the image level and 10 types of events at the semantic level. We have tested the proposed query language for the retrieval of surveillance videos of a metro station. In our experiments the database contains more than 200 indexed physical objects and 48 semantic events. The results using different types of queries are promising.