System and method of classifying events

Details System and method of classifying events System and method of classifying events

2011-08-23

2011-08-23

Gaffin, Jeffrey A (Department: 2129)

Data processing: artificial intelligence

Machine learning

C706S048000, C706S045000

Reexamination Certificate

active

08005767

ABSTRACT:
The present invention enables identification of events such as target. From training target event data the present a very large number of clusters are formed for each class based on Euclidean distance using a repetitive k-means clustering process. Features from each cluster are identified by extracting out their dominant eigenvectors. Once all of the dominant eigenvectors have been identified, they define the relevant space of the cluster. New target event data is compared to each cluster by projecting it onto the relevant and noise spaces. The more the data lies within the relevant space and the less it lies within the noise space the more similar the data is to a cluster. The new target event data is then classified based on the training target event data.

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Siskind et al., J., “A Maximum-Likelihood Approach to Visual Event Classification”, ECCV '96, pp. 347-360, 1996.

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