Abstract:
The paper presents an automatic relevance feedback method for improving retrieval accuracy in video databases. We first demonstrate a representation based on a template-f...Show MoreMetadata
Abstract:
The paper presents an automatic relevance feedback method for improving retrieval accuracy in video databases. We first demonstrate a representation based on a template-frequency model (TFM) that allows the full use of the temporal dimension. We then integrate the TFM with a self-training neural network structure to capture adaptively different degrees of visual importance in a video sequence. Forward and backward signal propagation is the key in this automatic relevance feedback method in order to enhance retrieval accuracy.
Published in: 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
Date of Conference: 06-10 April 2003
Date Added to IEEE Xplore: 21 May 2003
Print ISBN:0-7803-7663-3
Print ISSN: 1520-6149