| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
I. Koprinska and N. Kasabov
ABSTRACT
This paper reports an application of evolving fuzzy neural network (EFuNN) for camera operations recognition. EFuNN features one-pass learning, dynamical growing and shrinking architecture and ability to accommodate new knowledge without the need to retrain the network on both the original and new data. The network learns from pre-classified examples in the form of motion vector (MV) patterns, extracted from MPEG compressed video, in order to distinguish between six classes: static, panning, zooming, object motion, tracking and dissolve. The performance of EFuNN is compared with LVQ and the results are discussed. In addition, the impact of the number of membership functions and the contribution of the rule node aggregation are analyzed |
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