Time sequential imagery is difficult to analyze, because of its high dimesionality. This paper advances a new algorithm that screens input data in an intelligent way, discards data with negligible information and uses the remaining images to represent the sequence in an optimal compact form. We present data to illustrate how this algorithm can be used to do novelty filtering, novelty detection, segmentation, background independent modelling and classification.
"KL Techniques For Optimal Processing Of Time Sequential Imagery", Proc. SPIE 1007, Mobile Robots III, (10 March 1989); doi: 10.1117/12.949094; https://doi.org/10.1117/12.949094