Intelligent video editing system using a neural network coding scheme

Richard M. Rickman; T. John Stonham

doi:10.1117/12.205302

23 March 1995 Intelligent video editing system using a neural network coding scheme

Richard M. Rickman, T. John Stonham

Proceedings Volume 2420, Storage and Retrieval for Image and Video Databases III; (1995) https://doi.org/10.1117/12.205302
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

Video editors are frequently required to access sections of a video sequence which contain a particular scene. This may be regarded as an image retrieval-by-content problem where the user wishes to select images from within a large database according to a measure of similarity to a target. We present an intelligent video editing system based on a neural network coding scheme. The transformation learnt by the neural network maps each image into a very compact index which supports rapid fuzzy matching of video images. The neural network is trained using a learning law which produces an information preserving transform. Trained in this way, the node learns features which characterize the distribution of scenes within the video sequence. Each image frame in the sequence is coded with respect to these features. We show how the system performs on a typical sequence of newsreel footage and discuss the factors affecting the performance of both the training and the retrieval mechanism.

Citation Download Citation

Richard M. Rickman and T. John Stonham "Intelligent video editing system using a neural network coding scheme", Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); https://doi.org/10.1117/12.205302

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