VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Affinity-Based Probabilistic Reasoning and Document Clustering on the WWW
COMPSAC '00 24th International Computer Software and Applications Conference
Hidden Markov Model Parsing of Video Programs
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Color image retrieval based on hidden Markov models
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Multimedia data, typically image data, is increasing rapidly across the Internet and elsewhere. To keep pace with the increasing volumes of image information, new techniques need to be investigated to retrieve images intelligently and efficiently. Content-based image retrieval is always a challenging task. In this paper, a stochastic model, called Markov Model Mediator (MMM) mechanism, is used to model the searching and retrieval process for content-based image retrieval. Different from the common methods, our stochastic model carries out the searching and similarity computing process dynamically, taking into consideration not only the image content features but also other characteristics of images such as their access frequencies and access patterns. Experimental results demonstrate that the MMM mechanism together with the stochastic process can assist in retrieving more accurate results for user queries.