Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
Semantic representation: search and mining of multimedia content
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Effective automatic image annotation via a coherent language model and active learning
Proceedings of the 12th annual ACM international conference on Multimedia
Using dual cascading learning frameworks for image indexing
VIP '05 Proceedings of the Pan-Sydney area workshop on Visual information processing
Learning rich semantics from news video archives by style analysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A framework for moderate vocabulary semantic visual concept detection
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Semantics reinforcement and fusion learning for multimedia streams
Proceedings of the 6th ACM international conference on Image and video retrieval
An empirical study of inter-concept similarities in multimedia ontologies
Proceedings of the 6th ACM international conference on Image and video retrieval
Correlative multi-label video annotation
Proceedings of the 15th international conference on Multimedia
Video event mining and content management system using shot ontology description
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Activity based surveillance video content modelling
Pattern Recognition
Automated hierarchical image segmentation based on merging of quadrilaterals
ISCGAV'06 Proceedings of the 6th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Leveraging probabilistic season and location context models for scene understanding
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Semantic representation of multimedia content: Knowledge representation and semantic indexing
Multimedia Tools and Applications
Correlative multilabel video annotation with temporal kernels
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
State-of-the-art on spatio-temporal information-based video retrieval
Pattern Recognition
Multi-cue fusion for semantic video indexing
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Collaborative learning for image and video annotation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Multimedia Tools and Applications
Movie story intensity representation through audiovisual tempo analysis
Multimedia Tools and Applications
Foundations and Trends in Information Retrieval
Semi-automatic dynamic auxiliary-tag-aided image annotation
Pattern Recognition
Content-based attention ranking using visual and contextual attention model for baseball videos
IEEE Transactions on Multimedia - Special issue on integration of context and content
On supervision and statistical learning for semantic multimedia analysis
Journal of Visual Communication and Image Representation
Combining intra-image and inter-class semantics for consumer image retrieval
Pattern Recognition
A hybrid framework for detecting the semantics of concepts and context
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Modal keywords, ontologies, and reasoning for video understanding
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Minimizing uncertainty in semantic identification when computing resources are limited
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Event detection and recognition using histogram of oriented gradients and hidden markov models
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Ensemble multi-instance multi-label learning approach for video annotation task
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Ensemble approach based on conditional random field for multi-label image and video annotation
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Automatic image semantic annotation based on image-keyword document model
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Braving the semantic gap: mapping visual concepts from images and videos
ICDM'04 Proceedings of the 4th international conference on Advances in Data Mining: applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications
From partition trees to semantic trees
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Collaborative video reindexing via matrix factorization
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Multimedia retrieval and classification for web content
FDIA'07 Proceedings of the 1st BCS IRSG conference on Future Directions in Information Access
Temporal-Spatial refinements for video concept fusion
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Semantic context based refinement for news video annotation
Multimedia Tools and Applications
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Video query by semantic keywords is one of the most challenging research issues in video data management. To go beyond low-level similarity and access video data content by semantics, we need to bridge the gap between the low-level representation and high-level semantics. This is a difficult multimedia understanding problem. We formulate this problem as a probabilistic pattern-recognition problem for modeling semantics in terms of concepts and context. To map low-level features to high-level semantics, we propose probabilistic multimedia objects (multijects). Examples of multijects in movies include explosion, mountain, beach, outdoor, music, etc. Semantic concepts in videos interact and appear in context. To model this interaction explicitly, we propose a network of multijects (multinet). To model the multinet computationally, we propose a factor graph framework which can enforce spatio-temporal constraints. Using probabilistic models for multijects, rocks, sky, snow, water-body, and forestry/greenery, and using a factor graph as the multinet, we demonstrate the application of this framework to semantic video indexing. We demonstrate how detection performance can be significantly improved using the multinet to take inter-conceptual relationships into account. Our experiments using a large video database consisting of clips from several movies and based on a set of five semantic concepts reveal a significant improvement in detection performance by over 22%. We also show how the multinet is extended to take temporal correlation into account. By constructing a dynamic multinet, we show that the detection performance is further enhanced by as much as 12%. With this framework, we show how keyword-based query and semantic filtering is possible for a predetermined set of concepts