VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Communications of the ACM
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
A New Tree Type Data Structure with Homogeneous Nodes Suitable for a Very Large Spatial Database
Proceedings of the Sixth International Conference on Data Engineering
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Partial Image Retrieval Using Color Regions and Spatial Relationships
Proceedings of the IFIP TC2/WG2.6 Sixth Working Conference on Visual Database Systems: Visual and Multimedia Information Management
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A fully automated content-based video search engine supporting spatiotemporal queries
IEEE Transactions on Circuits and Systems for Video Technology
Construction of interactive video information system by applying results of object recognition
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
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In this paper, we present a semantic retrieval and semi-automatic annotation system for movies, based on the regional features of video images. The system uses a 5-dimensional GBD-tree structure to organize the low-level features: the color, area, and minimal bounding rectangle coordinates of each region that is a segment of a key frame. We propose a regionally based "semantic" object retrieval method that compares color, area, and spatial relationships between selected regions to distinguish them from background information. Using this method, movie information can be retrieved for video data containing the same objects based upon object semantics. In addition, a semi-automatic annotation method is proposed for annotating the matched "semantic" objects for further use. A retrieval system has been implemented that includes semantic retrieval and semi-automatic annotation functions.