Fans of live poker may soon be able to get a better read on their opponents thanks to the development of advanced facial recognition computer program.
According to recent reports, Xiaobai Li and his team at the University of Oulu in Finland have developed a new machine that’s able to read microexpressions and interpret them in a way humans can’t replicate.
Although Phil Hellmuth believes he has the best reading abilities in the world, Li would argue that his machine is not only better than the Poker Brat, but better than anyone else on the planet.
Profiled in a variety of tech publications, including the MIT Technology Review, Li’s machine is reportedly able to pick and analyze thousands of microexpressions.
Until now this type of technology has been limited in its ability to read human expressions. Traditionally, researchers in this field had chosen to record participants carrying out staged expressions.
Asking people to act in various ways, such as “happy”, “sad” or “indifferent”, researchers would then record the expressions each participant made.
However, according to the experts, this system is flawed because micro-expressions are, by definition, a lot more subtle.
In fact, even before we’ve expressed a certain emotion, our faces and gestures will respond in microscopic ways which often giveaway our state of mind.
To capture this phenomenon in a more accurate way, Li and his team created a scenario where participants were better off repressing their emotions.
By telling the group of 20 participants that they would have to answer a lengthy questionnaire about every emotion they showed, Li was able to stop them from being too obvious with their emotional responses to various situations.
By creating this dynamic, Li was able to capture thousands of microexpressions and record it in the system’s database. With more information now stored in its memory bank, Li’s machine was then able to outperform humans in a variety of facial recognition tasks.
For poker players looking to improve their results, being able to read micro-expressions could be extremely useful.
Of course, it could be a long time before Li’s software is available in a portable format, but there are already suggestions that it could be incorporated into Google’s glass technology.
Despite being shelved for the time being pending further development, Google Glass looks set to make the procurement of information even more efficient in the coming years.
If this is the case then facial recognition technology such as Li’s could become an integral part of the product in the future.
Although poker room directors would likely insist that Google Glasses not be worn at the table if this sort of technology was available, it’s certainly a sign that the way in which we view micro-expressions could be changing and that could take reading poker tells to a whole new level.