Machine Perception Technologies:

We are a new start up company dedicated to the development of Machine Perception Technologies for You.


Smile Analysis

Anatomy of the Smile. The upper and lower lips frame the display zone of the smile. Within this framework, the components of... 

Fatigue Detection

Driver fatigue detection is determined by monitoring the driver’s grip force on the steering wheel, based on the variation... 

Facial Expression Analysis

Facial expression communicates information about emotions, regulates interpersonal behavior and person perception, indexes physiologic...



We launched SMILE for Android

We just launched our first version of SMILE for Android. It detects smiles, ranks them and puts them in a world map. You can get it for $0.99 at the Google Android Store. (Just type Smile for Android on Google).

NOTE:  We are no longer operational. No products are available.


Some Background on Facial Recognition Technology


Just imagine if expert humans or face-reading machines were at the airports where the 9/11 hijackers had boarded their doomed planes. Perhaps thousands of lives would have been saved on 9/11 if the emotional states of hijackers had been correctly deducted.  According to says San Francisco-based psychologist Paul Ekman detainments would have been triggered. Unfortunately there were no expert humans or face-reading machines being used.

Tim Roth’s character in the Fox TV series Lie To Me was based on Paul Ekman and his work.  Since 9/11, Ekman has worked with the Central Intelligence Agency (CIA), the Department of Homeland Security (DHS), the Department of Defense (DOD), among others to help train people, and develop machines that can read faces for emotions with the goal of preventing disastrous events occurring at all levels.

Additional facial recognition applications could include assisting Transportation Security Administration (TSA) agents screen for potential terrorists at airports, or teaching U.S. Army Special Forces in Afghanistan and elsewhere how to determine an enemy combatant’s veracity or his/ her intent to kill. Ekman slap has provided training to a number of guards at Abu Ghraib prison.  By using his facial analysis work, guards were better able to extract information without the use of torture.

Paul Ekman was a pioneer in the field of facial emotion measurement and the neuro-scientific areas, which overlaps with both face-recognition and neuro-marketing.  Along with the Dalai Lama, Ekman has written a book, Emotional Awareness. Universally credited with developing the Facial Action Coding System (FACS).  FACS is the comprehensive dictionary of facial expression measurements. It has become the scientific underpinning for human observation and automated facial analysis internationally as well as across a variety of academic and commercial fields. For instance, both Microsoft and Apple are building their own facial recognition capabilities, as has Google. In some school districts his methodology is being put to work particularly for better understanding those with cognitive disabilities. And it can enable people to be more in tune with their emotions.

According to Ekman there are two basic ways to measure facial emotion. You can use specially trained people to analyze facial micro-expressions and emotions or use a technological, automated method. He prefers using the human approach when time is of the essence such as in life and death instances involving and law enforcement officers, intelligence, or military situations. He believes it is significantly more accurate than relying on an automated method.  However, one of the fallacies of using humans is that they can become fatigued. In addition, their levels of observation or interpretation can vary considerably. However, using the technology for laborious, frame-by-frame video analysis also has its place, particularly as a backup system. 

Ekman, presently sits on the board of a nascent company, which specializes in automating facial expressions analysis based on his FACS foundation. The CIA has been studying the efficacy of the automating micro-expressions analysis methodology of Machine Perception Technologies (MPT) "Neural Network" versus other alternative methods. MPT's splits it work between the "security" arena and marketing for such companies as Procter & Gamble, Intel, and Sony. One of the main goals of MPT is in advancing "machine learning" and creating smarter, more natural interaction and interfaces between humans and machines.

Affectiva, another company whose methodology is based on Ekman’s FACS  advertises itself as an emotion measurement technology company.  Affectiva's initial focus has been in health care. They have developed tools, which help people on the autism spectrum to communicate as well as applications that have developed tools that help those on the autism spectrum to communicate and applications, via skin and facial sensors that allow people to self-monitor their anxiety level or heart rate. Following the money, Affectiva has been busy consulting marketing and media clients regarding their advertising and consumer engagement. However, according to their COO, Affectiva will never focus on security and deception. Instead they want people to be more aware of their emotions and empowered to better manage and improve their moods, health, work, socializing and life. They say their focus is on doing good in the world with the broadest applications.

There are critics of this field that encompasses facial expression measurements via both human and technology. They feel it opens the doors to big brother intrusions, sinister mind reading, and phony junk science with low accuracy, and/or high expenses.

Even though there are differences in their methods, services and views, all of the facial emotion measurement experts their companies agree that new applications will emerge that cannot even be imagined today, but will forever change the way we do things in the future.