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A novel cost-effective skin-tone detector for consumer devices
Skin-tone detection has received considerable attention in recent years and applied in wide
range of image processing and computer vision applications. The objective of this research
project is to develop a real-time skin-tone detection solution optimized for consumer devices,
allows for a deliverance of high detection performance at minimal computational costs. The
proposed solution will deliver reliable and robust performance even under varying illumination
conditions and unconstrained complex background. Key challenge faced by researchers dealing
with skin tone detection includes selection of a model of skin color distribution and a color
space. Addressing this challenge requires collaborative research which involves academia and
industry. We will carry out comparative evaluation of various skin-tone detectors in terms of
detection performance and computational complexity to identify the best algorithms suit for our
requirements. Consequently, the proposed research will allow us to develop a low complexity
skin-tone detection module, enabling robust real-time detection in consumer grade devices.
Faculty Supervisor:
Konstantinos (Kostas) Plataniotis
Student:
Partner:
Qualcomm Canada Inc
Discipline:
Computer science
Sector:
Information and cultural industries; Manufacturing; Professional, scientific and technical services
University:
University of Toronto
Program:
Accelerate
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