A low complexity face recognition for consumer devices

Due to the rapid growth of consumer grade devices and corresponding application market, the incorporation of

vision capabilities into embedded systems has gained significant attention from researchers lately. Similarly to

the human visual system, embedded computer vision systems analyze and extract information from visual

content in a wide variety of products. Face recognition has been one of the most successful applications in this

field. A cost effective implementation of reliable face recognition (FR) solutions can be useful for a wide range

of applications, such as identity authentication, entertainment, and content based retrieval system. However,

embedded system based face recognition solutions often suffer from not only common problems such as

variation in illumination (pose variation does not appear to be a problem for face recognition at a short distance),

but also relatively low quality input face images, and limited computational resources. Although many

researchers have attempted to develop robust FR algorithms, relatively few initiatives have been undertaken to

adapt FR solutions………………………………………

Faculty Supervisor:

Konstantinos (Kostas) Plataniotis

Student:

Partner:

Qualcomm Canada Inc

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

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Mitacs Partners