EPFL scientists are studying how to identify drivers' emotions using embedded cameras that film their faces
Technology now allows us to read facial expressions and identify which of the seven universal emotions a person is feeling: fear, anger, joy, sadness, disgust, surprise, or suspicion. This is very useful in video game development, medicine, marketing, and, perhaps less obviously, in driver safety. We know that in addition to fatigue, the emotional state of the driver is a risk factor.
The device detects anger on the driver's face.
Credit: EPFL-LTS5 & PSA
Irritation, in particular, can make drivers more aggressive and less attentive. EPFL researchers, in collaboration with PSA Peugeot Citroën, have developed an on-board emotion detector based on the analysis of facial expressions. Tests carried out using a prototype indicate that the idea could have promising applications.
It's not easy to measure emotions within the confines of a car, especially non-invasively. The solution explored by scientists in EPFL's Signal Processing 5 Laboratory (LTS5), who specialize in facial detection, monitoring and analysis, is to get drivers' faces to do the job. In collaboration with PSA Peugeot Citroën, LTS5 adapted a facial detection device for use in a car, using an infrared camera placed behind the steering wheel.
The problem was to get the device to recognize irritation on the face of a driver. Everyone expresses this state somewhat differently – a kick, an epithet, a nervous tic or an impassive face. To simplify the task at this stage of the project, Hua Gao and Anil Yüce, who spearheaded the research, chose to track only two expressions: anger and disgust, whose manifestations are similar to those of anger.
Two phases of tests were carried out. First, the system "learned" to identify the two emotions using a series of photos of subjects expressing them. Then the same exercise was carried out using videos. The images were taken both in an office setting as well as in real life situations, in a car that was made available for the project.
The rapidity with which the comparison between filmed images and thus detection could be carried out depended on the analysis methods used. But overall, the system worked well and irritation could be accurately detected in the majority of cases. When the test failed, it was usually because this state is very variable from individual to individual. This is where the difficulty will always lie, given the diversity of how we express anger. Additional research aims to explore updating the system in real-time – to complement the static database – a self-taught human-machine interface, or a more advanced facial monitoring algorithm, says Hua Gao.
Detecting emotions is only one indicator for improving driver safety and comfort. In this project, it was coupled with a fatigue detector that measures the percentage of eyelid closure. The LTS5 is also working on detecting other states on drivers' faces such as distraction, and on lip reading for use in vocal recognition. These projects are coordinated by EPFL's Transportation Center and carried out in collaboration with PSA Peugeot Citroën.
Jean-Philippe Thiran | EurekAlert!
New study shows nanoscale pendulum coupling
05.07.2019 | University of Barcelona
New unprinting method can help recycle paper and curb environmental costs
26.06.2019 | Rutgers University
Scientists at the University Würzburg and University Hospital of Würzburg found that megakaryocytes act as “bouncers” and thus modulate bone marrow niche properties and cell migration dynamics. The study was published in July in the Journal “Haematologica”.
Hematopoiesis is the process of forming blood cells, which occurs predominantly in the bone marrow. The bone marrow produces all types of blood cells: red...
For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.
Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...
An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".
The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...
An interdisciplinary research team at the Technical University of Munich (TUM) has built platinum nanoparticles for catalysis in fuel cells: The new size-optimized catalysts are twice as good as the best process commercially available today.
Fuel cells may well replace batteries as the power source for electric cars. They consume hydrogen, a gas which could be produced for example using surplus...
The fly agaric with its red hat is perhaps the most evocative of the diverse and variously colored mushroom species. Hitherto, the purpose of these colors was...
24.06.2019 | Event News
29.04.2019 | Event News
17.04.2019 | Event News
17.07.2019 | Earth Sciences
17.07.2019 | Information Technology
17.07.2019 | Materials Sciences