History of Face Recognition

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The History of Face Recognition

From Wikipedia

Computer vision can be described as the study of methods which can be used for allowing computers to "understand" images, or multidimensional data in general.

Over 30 years of research has gone into the study of Computer Vision, but it is still a field largely in its infancy. The largest contributing factor to this slow advancement is that the process that extracts 3-D information from 2-D images is much more complex than the flipside science, Computer Graphics. A computer has an easier time translating 3-D information into 2-D imaging.

In addition to the overall complexity, the lack of consumer application of the process slows down progress of development...until now.

Face recognition has been heavily studied within the field of Computer Vision over the past decade. The difficulties of face recognition lie in the inherent variation of facial characteristics and the environment of image acquisition. The following summarizes the major variations in the images of a single individual:

• 3D poses, image scaling, and view point
• Changes in the actual faces: closing of the eyes, wearing glasses,facial expression, facial hair, aging, make-up, and perspiration
• Partial occlusion
• Light source strength, direction, and distribution

Most of the existing face recognition systems to date usually impose restrictions to avoid those difficulties on the imaging situation, such as well-controlled environments or near-frontal, well-aligned images.

However, how many digital photos do you have that are shot straight-on in well-controlled environments? Exactly. That is why our team has been working so hard at getting the balance just right in achieving highest level of accuracy with the highest level of recognition possible.

S. Burak Gokturk is the co-founder and Chief Technology Officer of Riya. Prior to Riya, he developed computer vision algorithms at Canesta, Stanford, Intel, BEKO and Bogazici. He has been in the vision field for more than 8 years, and published more than 30 papers, and holds more than 15 patent applications.

Burak has assembled a team of experts in face and text recognition. This group of Ph.D.'s are developing amazing breakthrough technology that narrows the variables and attributes to more successfully detect and recognize the right people within your photos. Most significantly, the research that they are applying to Riya's technology today could be breakthrough technology in the overall field of Computer Vision.

Face and text recognition are just part of the overall scope that Riya wishes to achieve in their vision of mastering visual search online.

This isn't just visual search, folks, this is a breakthrough on the consumer application end of Computer Vision. You get to use it first. Are you stoked?

• Late 50's - Computer vision was born: Primitive tests on pixels using smoothing and edge detection techniques
• 60's/70's - Began incorporating other sciences like statistics, linear algebra and algorithms to the study
• 70's - Face recognition studies began
• Late 80's - Eigenface algorithm breakthrough. Feature vectors are discovered and features are broken out into combinations. The theory is that every face is made up of variations of features.
• 90's - Optical Character Recognition (OCR) launched for consumer applications like scanning and faxing.
• 00's - creates a greater push for the field of Computer Vision to be developed in the security areas
• 05 - Munjal Shah has this crazy idea that he wants to search his photos more effectively, gets introduced to Burak and they form Riya together with Azhar Khan.

Stay tuned for the future...!