Facial recognition software has improved by leaps and bounds over
the past few decades, with error rates decreasing significantly
within the past ten years. Though this is true, conditions such as
poor lighting, obstructions, and profile-only angles have continued
to persist in preventing wholly accurate readings. Face Recognition
in Adverse Conditions examines how the field of facial recognition
takes these adverse conditions into account when designing more
effective applications by discussing facial recognition under real
world PIE variations, current applications, and the future of the
field of facial recognition research. The work is intended for
academics, engineers, and researchers specializing in the field of
facial recognition.
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