Stimulus representations that are invariant under invertible transformations of sensor data

David N. Levin M.D.

doi:10.1117/12.431054

3 July 2001 Stimulus representations that are invariant under invertible transformations of sensor data

David N. Levin M.D.

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431054
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

Humans have a remarkable ability to perceive the constancy of a stimulus even though its appearance has changed to factors that are extrinsic to it. This paper shows how sensory devices can invariantly represent stimuli, even though their sensor state may have been transformed by factors extrinsic to the stimuli. Such transformations may be caused by changes of observational conditions such as: 1) alterations of the device's sensory apparatus, 2) changes in the observational environment external to the sensory device and the stimuli, and 3) modifications of the presentation of the stimuli themselves. The stimulus representations are invariant because they describe certain relationships of each sensor state to the time series of recently encountered sensor states, and these relationships are unchanged by any invertible transformation of sensor states. This paper describes three analytic methods of creating such representations, utilizing tensor calculus, affine-connected differential geometry, respectively. These techniques may be useful for designing a representation engine that comprises the front end of an intelligent sensory device. It could create stimulus representations that are amenable to pattern analysis because they are not affected by many factors that are extrinsic to the stimuli.

Citation Download Citation

David N. Levin M.D. "Stimulus representations that are invariant under invertible transformations of sensor data", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431054

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