Facilitate knowledge communications
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Semantic video classification by integrating flexible mixture model with adaptive EM algorithm
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Object Level Frame Comparison for Video Shot Detection
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
The Indiana Center for Database Systems at Purdue University
ACM SIGMOD Record
The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using object and trajectory analysis to facilitate indexing and retrieval of video
Knowledge-Based Systems
Manifold Learning Based Cross-media Retrieval: A Solution to Media Object Complementary Nature
Journal of VLSI Signal Processing Systems
OM-based video shot retrieval by one-to-one matching
Multimedia Tools and Applications
Proceedings of the 6th ACM international conference on Image and video retrieval
Video diver: generic video indexing with diverse features
Proceedings of the international workshop on Workshop on multimedia information retrieval
Foundations and Trends in Information Retrieval
Ranking with local regression and global alignment for cross media retrieval
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Multi-modal Correlation Modeling and Ranking for Retrieval
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
An efficient video indexing and retrieval algorithm using the luminance field trajectory modeling
IEEE Transactions on Circuits and Systems for Video Technology
Sports video mining via multichannel segmental hidden Markov models
IEEE Transactions on Multimedia
Cross-media retrieval using query dependent search methods
Pattern Recognition
A video retrieval algorithm using random projections
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Combining location and feature information for multimedia retrieval
International Journal of Computer Applications in Technology
IEEE Transactions on Information Technology in Biomedicine
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
A Bayesian network modeling approach for cross media analysis
Image Communication
Bridging the gap between visual and auditory feature spaces for cross-media retrieval
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Boosting cross-media retrieval by learning with positive and negative examples
MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
Measuring multi-modality similarities via subspace learning for cross-media retrieval
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Fast and robust short video clip search for copy detection
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Football video segmentation based on video production strategy
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Understanding multimedia document semantics for cross-media retrieval
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Flexible content extraction and querying for videos
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
Object-based surveillance video retrieval system with real-time indexing methodology
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
A conceptual framework for automatic text-based indexing and retrieval in digital video collections
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Zero-shot video retrieval using content and concepts
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Frontiers of Computer Science: Selected Publications from Chinese Universities
An analytical framework for event mining in video data
Artificial Intelligence Review
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Recent advances in digital video compression and networks have made video more accessible than ever. However, the existing content-based video retrieval systems still suffer from the following problems. 1) Semantics-sensitive video classification problem because of the semantic gap between low-level visual features and high-level semantic visual concepts; 2) Integrated video access problem because of the lack of efficient video database indexing, automatic video annotation, and concept-oriented summary organization techniques. In this paper, we have proposed a novel framework, called ClassView, to make some advances toward more efficient video database indexing and access. 1) A hierarchical semantics-sensitive video classifier is proposed to shorten the semantic gap. The hierarchical tree structure of the semantics-sensitive video classifier is derived from the domain-dependent concept hierarchy of video contents in a database. Relevance analysis is used for selecting the discriminating visual features with suitable importances. The Expectation-Maximization (EM) algorithm is also used to determine the classification rule for each visual concept node in the classifier. 2) A hierarchical video database indexing and summary presentation technique is proposed to support more effective video access over a large-scale database. The hierarchical tree structure of our video database indexing scheme is determined by the domain-dependent concept hierarchy which is also used for video classification. The presentation of visual summary is also integrated with the inherent hierarchical video database indexing tree structure. Integrating video access with efficient database indexing tree structure has provided great opportunity for supporting more powerful video search engines.