Enhanced Sensory Perception:

As the population ages, acuity in one or more sensory channels often diminishes or may be totally lost. Augmenting or compensating for loss in the perceptual system by taking advantage of sensory data outside the normal human range and mapping it to meaningful perceptual information has the potential of giving an ordinary person enhanced sensory perception (ESP).

Sensory deficiency is not restricted to any particular segment of the population, however.  For example, we tend to be myopic about ourselves, and thus can benefit from psychological mirrors in the form of trainers or therapists who can assess and guide our physical and/or mental development. In this spirit, "Reflective Biometrics" is a novel approach to analyzing and interpreting biometric sensory information for self monitoring and examination.  It is self-examination via technology as a mirror. Biometric technologies in service of the individual can serve as reflectors that enhance our self-awareness, self-understanding, and health, and they can facilitate our interaction with computers and with each other by augmenting our perceptual system.

Perceptual Signatures:

• Perceptual signatures encode identifiers implicit in our facial features, gaits, communication styles, behaviors, daily activities, etc.
  
  
• Perceptual signatures come in a variety of forms, such as a spending profile that banks can use to identify fraudulent spending, a characteristic gesture that comedians exploit, a human motion signature for computer animation, a facial signature that can be identified by keyless access systems, etc.



• Perceptual signatures research has produced innovative algorithms based on statistical machine learning and numerical tensor algebra for extracting perceptual signatures from large datasets, generated by individuals or groups of people, corporations, government agencies, terrorist cells, etc.

Biometric Computing using Perceptual Signatures:

Perceptual signatures distilled from biometric data is fundamental to human-centric technologies such as the burgeoning security industry, but when directed at ourselves, biometric technologies can serve as reflectors that enhance our self-awareness, understanding, and health, and they can facilitate our interaction with each other and computers.

• Reflective Biometrics distills biometric data to perceptual signatures for self-surveillance. This can enable self-monitoring (the sci-fi Heechee Saga - the future for at-home health care.) Self-surveillance systems can become instruments of the individual. Reflective biometrics research is the self-examination via technology as a mirror.



• TensorFaces for recognition is an individual's identifier extracted from unconstrained facial images that can confuse and mislead facial recognition systems. Tensor representations of facial images enable robust facial recognition under unconstrained viewpoint, illumination, expression, and other conditions.



• Human Motion Signatures is a qualitative and quantitative model of human motion that can be used to identify an individual or characterize the gait as normal versus pathological. Multilinear algebra is applied to the nonlinear representation, analysis, synthesis, and recognition of human movement from perceptual data.

 

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