Dr Guoying Zhao and Prof. Matti Pietikäinen from the Machine Vision Group of the University of Oulu have produced significant results in their research focusing on facial expression analysis through video images. They have developed two new descriptors for dynamic texture recognition and applied them to facial expression analysis.
Their article “Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions” was recently accepted for publication in the journal IEEE Transactions on Pattern Analysis and Machine Intelligence, one of the most-cited journals in electrical engineering and computer science. The journal ranks among the top journals in these fields.
The developed approach can be used in automatic and real-time facial expression recognition, and it has many potential computer vision applications. These include advanced human-computer interaction, biometric recognition, telecommunications and psychological research. For example, a machine able to recognise human emotions may soon be reality.
The approach combines motion and appearance data in a way that avoids interference from illumination variations and image transformations such as rotation. The method is theoretically and technically simple to implement.
Niko Rinta | alfa
New epidemic management system combats monkeypox outbreak in Nigeria
15.12.2017 | Helmholtz-Zentrum für Infektionsforschung
Gecko adhesion technology moves closer to industrial uses
13.12.2017 | Georgia Institute of Technology
DNA molecules that follow specific instructions could offer more precise molecular control of synthetic chemical systems, a discovery that opens the door for engineers to create molecular machines with new and complex behaviors.
Researchers have created chemical amplifiers and a chemical oscillator using a systematic method that has the potential to embed sophisticated circuit...
MPQ scientists achieve long storage times for photonic quantum bits which break the lower bound for direct teleportation in a global quantum network.
Concerning the development of quantum memories for the realization of global quantum networks, scientists of the Quantum Dynamics Division led by Professor...
Researchers have developed a water cloaking concept based on electromagnetic forces that could eliminate an object's wake, greatly reducing its drag while...
Tiny pores at a cell's entryway act as miniature bouncers, letting in some electrically charged atoms--ions--but blocking others. Operating as exquisitely sensitive filters, these "ion channels" play a critical role in biological functions such as muscle contraction and the firing of brain cells.
To rapidly transport the right ions through the cell membrane, the tiny channels rely on a complex interplay between the ions and surrounding molecules,...
The miniaturization of the current technology of storage media is hindered by fundamental limits of quantum mechanics. A new approach consists in using so-called spin-crossover molecules as the smallest possible storage unit. Similar to normal hard drives, these special molecules can save information via their magnetic state. A research team from Kiel University has now managed to successfully place a new class of spin-crossover molecules onto a surface and to improve the molecule’s storage capacity. The storage density of conventional hard drives could therefore theoretically be increased by more than one hundred fold. The study has been published in the scientific journal Nano Letters.
Over the past few years, the building blocks of storage media have gotten ever smaller. But further miniaturization of the current technology is hindered by...
11.12.2017 | Event News
08.12.2017 | Event News
07.12.2017 | Event News
15.12.2017 | Power and Electrical Engineering
15.12.2017 | Materials Sciences
15.12.2017 | Life Sciences