1. Applications · E-learning apps, changing the presentation style of an e-lesson according to the mood of the person. · Psychological health services, to detect the mood of the patient before the session starts. · Companion Devices, detecting the mood of the person to adjust the way the device interact with the person. · Affective mirrors, to tell how the person performs. · Social Monitoring, to detect the mood of a driver and alert other drivers. · Impact of TV advertisement, to analyze a consumer’s face when using a product (real time video recording). Francisco Chaparro. Olympia High School. Background The way we express our emotions with our faces are universal, and do not depend in which part of the world we were born or grew up. Facial expressions are biological and they each have their own characteristics. Happy teen boy Objectives To detect emotional information of an individual or group of individuals from images captured in video. How? 1.Facial expressions are captured with a video camera. 1.The video is analyzed and meaningful images are selected to be fed to a mathematical algorithm. 1.This mathematical algorithm detects facial expression detection and labels the image: anger, disgust, fear, happy, sad, and surprise. There are different methods to accomplish this task. We can use one or a combination of the following methods. 1.Optical Flow 1.Hidden Markow Model 1.Neural Network Processing 1.Active Appearance Model Challenges ●Facial expressions detected are not real. ●The technique works very well with frontal use but it does not in other cases. ●The label given to the image depends also on technical aspects such as processing power/capabilities and illumination Setup (Data gathering). Ion Portable Cameras Basic Emotions 6 cameras, 6 different people to captivate 6 different moods. Anger, Disgust, Happiness, Sadness, and Surprise, registered facial expressions of 6 students while watching different kind of videos. Applications ●E-learning apps, changing the presentation style of an e-lesson according to the mood of the person. ●Psychological health services, to detect the mood of the patient before the session starts. ●Companion Devices, detecting the mood of the person to adjust the way the device interact with the person. e-pets ● Affective mirrors, to tell how the person performs. ●Social Monitoring, to detect the mood of a driver and alert other drivers. ●Impact of TV advertisement, to analyze a consumer’s face when using a product (real time video recording). ●Technologies for people with autism. ●Selection of music based on person’s mood. Pictures References 1.N.p., n.d. Web. 22 July 2016. 2.N.p., n.d. Web. 22 July 2016..http://cache1.asset-cache.net/xt/183421144.jpg?v=1&g=fs1%7C0%7CEPL%7C21%7C144&s=1 3.N.p., n.d. Web. 22 July 2016..http://sr.photos3.fotosearch.com/bthumb/THK/THK011/c0031253.jpg 4.N.p., n.d. Web. 22 July 2016.. 5. N.p., n.d. Web. 22 July 2016.. 6. N.p., n.d. Web. 22 July 2016.. 7.N.p., n.d. Web. 22 July 2016.. 8.N.p., n.d. Web. 22 July 2016.. 9.N.p., n.d. Web. 22 July 2016. 10.N.p., n.d. Web. 22 July 2016.. 11.N.p., n.d. Web. 22 July 2016.. 12.N.p., n.d. Web. 22 July 2016.. 13.N.p., n.d. Web. 22 July 2016. 14.N.p., n.d. Web. 22 July 2016.. 15.N.p., n.d. Web. 22 July 2016..