首页|Researcher from Autonomous University of Queretaro Publishes Findings in Machine Learning (Automatic Segmentation of Facial Regions of Interest and Stress Detection Using Machine Learning)
Researcher from Autonomous University of Queretaro Publishes Findings in Machine Learning (Automatic Segmentation of Facial Regions of Interest and Stress Detection Using Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New study results on artificial intelligence have been published. According to newsoriginating from San Juan del Rio, Mexico, by NewsRx editors, the research stated, “Stress is a factor thataffects many people today and is responsible for many of the causes of poor quality of life. For this reason,it is necessary to be able to determine whether a person is stressed or not.”The news correspondents obtained a quote from the research from Autonomous University of Queretaro:“Therefore, it is necessary to develop tools that are non-invasive, innocuous, and easy to use. This paperdescribes a methodology for classifying stress in humans by automatically detecting facial regions of interestin thermal images using machine learning during a short Trier Social Stress Test. Five regions of interest,namely the nose, right cheek, left cheek, forehead, and chin, are automatically detected. The temperatureof each of these regions is then extracted and used as input to a classifier, specifically a Support VectorMachine, which outputs three states: baseline, stressed, and relaxed. The proposal was developed andtested on thermal images of 25 participants who were subjected to a stress-inducing protocol followed byrelaxation techniques. After testing the developed methodology, an accuracy of 95.4% and an error rateof 4.5% were obtained.”
Autonomous University of QueretaroSan Juan del RioMexicoNorth and Central AmericaCyborgsEmerging TechnologiesMachine Learning
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