Posted on Apr 3, 2018 | Rating

Real-time Facial Emotion Detection Software Component

The asset detects real-time emotion based on facial expression of humans. The asset functions in three manners: 1) using a single image file, 2) using a recorded video file, and 3) using a real-time webcam stream.

Short non-technical description: The asset will be useful for emotion-based game adaptation in both entertainment and applying digital games. For the player: to have emotionally tailored gameplay experiences; For the developer: to provide emotional assessment during playtesting.

Technical description: The asset uses the simple and low-cost device: standard webcam to detect facial expressions of the player. This asset uses emotion classification suggested by Ekman and Friesen (1978), which is widely used in psychological research and practice, comprising six basic emotions: happiness, sadness, surprise, fear, disgust, and anger. In addition, it includes the complement, which is the neutral emotion.

<p class="asset-property"><span class="text-caption">Detailed description:</span> This asset captures facial expressions of humans and provides six basic emotions (happy, sad, surprise, fear, disgust, and anger) as well as the neutral emotion, accordingly. The asset functions in three manners: 1) using a single image file, 2) using a recorded video file, and 3) using a real-time webcam stream. The asset can be used in different video games and in different domains. Moreover, it can be used in serious games and in interactive games. </p>

Date: Jan 1, 2017

Language: English

Access URL:






Facial expressions


Human-Computer Interaction


Game development environment: Unity

Target platform: Windows

Programming language: C#

Version: 1.0

Version notes: Alpha version, Uses DLIB for face detection and landmarks detection.

Development status: Completed

Commit URL:

Type: Apache 2.0 (Apache License 2.0)


Personal skills Effectiveness Flexibility Self-confidence Self-control and Stress Resistance Recognize objects Learn new tasks willingly and Lifelong learning Self-discipline Self-reflection
Computers in other domains Computer games
Education Distance learning E-learning Interactive learning environments
Life and medical sciences Health care information systems
Component Affective State Detection

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