Current technologies can track our position on the planet to the mood of our co-workers in the office. Trendy “Apps” come in the shape of friendly interfaces installed in portable devices posing no harm at first sight. But what happens when such technologies are used for marketing and commercial purposes? Maja Pantic presents her current developments in the field of behavioural computing and machine analysis of human non-verbal behaviour, complemented by the industrial approach of Elnar Hajiyev. The complex nature and uncanny future of affective analytics will be portrayed by the artistic work of filmmaker and programmer Ruben van de Ven. Sam Tims, 12grapes, Recruiting Specialist Maja Pantic, Prof. of Affective & Behavioural Computing at ICL Elnar Hajiyeb, Co-founder of Realeyes Ruben van de Ven, Filmmaker, Programmer, Artist Fri 4.11.2016, 14:30 – 16:00 created by State Festival http://www.statefestival.org/ presented by F.A.Z. http://www.faz.net/ produced by WECAP http://wecap.de/ Creative Commons Attribution-ShareAlike 3.0 Germany (CC BY-SA 3.0 DE)
Tests of the Emotion Detector created in Python. As it can be seen, the detector prioritizes neutral and happiness expressions (this was due to the datasets employed in the creation of the detector; they had many more samples of these expressions than the others). The complete source code (under MIT license) is available in Github: https://github.com/luigivieira/emotions The original video used in the tests is the Human Emotions, used and reproduced here with the kind authorization from the folks of the Imagine Pictures video production company (thank you guys!). Original URL of the video: https://www.youtube.com/watch?v=UjZzdo2-LKE
View full lesson: http://ed.ted.com/lessons/can-machines-read-your-emotions-kostas-karpouzis Computers can beat us in board games, transcribe speech, and instantly identify almost any object. But will future robots go further by learning to figure out what we’re feeling? Kostas Karpouzis imagines a future where machines and the people who run them can accurately read our emotional states — and explains how that could allow them to assist us, or manipulate us, at unprecedented scales. Lesson by Kostas Karpouzis, animation by Lasse Rützou Bruntse.
An iOS app that can detect human emotions, objects and lot more. Made using coreML image detection API. Thank you for Watching. Please don’t forget to subscribe. ~ ## Inspiration Inspired by a few blind people who use echolocation to “see” things around them, we have developed an interface that would help a blind person listen to have a feeling of where they belong in the society and enjoy the little things and experiences of everyday life. ## What it does The interface is connected to a camera (which could be then possibly integrated with cameras on pen tips) which records real time videos of events, parse it into multiple frames – analyze it piece by piece and finally using a text to speech interface, dictates what it sees. ## How we built it For Building the interface, we used the Apple Artificial Intelligence API that contains a pre-trained data set that could be readily used. However on experimenting we learned that real time video/image has a lot of noise, and that it would take a long time to train the data set for practical purposes. Therefore we created a small data set with real time images (taken using phone cameras) and further trained the available data set to a considerable degree of accuracy. With enough time, this can further be implemented and generalized into more diverse data sets, achieving its intended purpose. ## Challenges we ran into As previously mentioned, we learned that the time it takes to train [More]
Emotion Research LAB´s facial recognition software captures the emotions in real time of a consumer while testing a yogurt. The obtained data are included in the study along with the measurement of the emotions of the rest of the individuals. The final report includes the key metrics for observing the main satisfaction level.
Machines are already very good at recognising human emotions when they have a static, frontal view of a person’s face. Maja Pantic, Professor of Affective and Behavioral Computing at Imperial College London, shares progress towards identifying people’s emotions “in the wild” and discusses possible applications, from marketing to medicine. http://www.weforum.org/
Click looks at emotion-detecting technology, mind-controlled movies and facial recognition systems used for the Royal Wedding. Subscribe HERE http://bit.ly/1uNQEWR Find us online at www.bbc.com/click Twitter: @bbcclick Facebook: www.facebook.com/BBCClick
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