Affectiva Facial Coding SDK

Incorporate Real-Time Emotion Sensing In Digital Experiences and Applications

Develop Emotion Sensing Solutions with Facial Coding SDK

Affectiva Facial Coding SDK is the industry-leading solution for real-time facial expression analysis, enabling businesses, researchers, and developers to decode human emotions with precision. Leveraging deep learning models trained on thousands of diverse participants, Affectiva Facial Coding SDK provides highly accurate emotion detection, outperforming competitors in real-world conditions.

Whether you’re conducting ad testing, user experience research, driver monitoring, or healthcare studies, Affectiva Facial Coding SDK delivers scalable, cross-platform emotion AI that integrates seamlessly into your workflow.

Comprehensive Data Set

17M

Faces

9B

Facial Frames

90

Countries Represented

What it can do

Facial Expression Analysis from any video source

Embed into your own application

Detect and analyze multiple faces simultaneously

Speaker detection for video conferences

Real-time and post-processing options

Mobile SDK coming soon

Try it out!

Open the playground and see how the technology works in real-time. Please note that the demo runs on a slightly older version of the SDK.

Why Choose The Affectiva Facial Coding SDK Over Competitors?

🔹 Comprehensive Emotion and Mood Detection – Recognizes 7 basic emotions plus two additional states: sentimentality and confusion, making it ideal for advertising, gaming, and market research.

🔹 Advanced Facial Action Unit (AU) Detection – Tracks 20+ AUs based on the Facial Action Coding System (FACS), ensuring a nuanced understanding of facial expressions beyond simple emotions.

🔹 Superior Accuracy in Real-World Conditions – Trained on a large-scale, naturalistic dataset, Affectiva Facial Coding SDK outperforms state-of-the-art competitors in challenging conditions, including diverse demographics, lighting, and occlusions.

🔹 Real-Time Processing on Multiple Faces – Optimized for high-speed, real-time analysis, supporting multi-face tracking for dynamic group interactions.

🔹 Seamless Integration Across Platforms – Available for Windows and Linux, Affectiva Facial Coding SDK easily integrates into research, business intelligence, and AI applications.

🔹 Proven Impact in Market Research & UX Testing – Used by global brands and research teams to measure audience engagement, emotional responses, and attention levels, driving data-driven decisions. Mentioned in 7k+ academic articles and papers.

🔹 Runs locally so no need for internet connectivity or specialized hardware. Affectiva Facial Coding SDK supports both Windows and Linux.

Who Uses Affectiva Facial Coding SDK?

Marketing and Advertising

Optimize ad engagement, emotional impact, and brand perception with emotion- driven insights.

User Experience & HCI Research

Enhance digital experiences by understanding user frustration, satisfaction, and engagement.

Automotive & Driver Monitoring

Detect driver drowsiness, distraction, and emotional states for safer road experiences.

Healthcare & Mental Health Applications

Support patient diagnostics, therapy monitoring, and psychological research with facial expression analysis.

Academic & AI Research

Train machine learning models with robust facial expression datasets, improving AI-human interaction capabilities.

Get Started with Affectiva Facial Coding SDK

Ready to integrate real-time facial expression analysis into your projects? Contact iMotions today to discuss licensing options, integration support, and custom solutions tailored to your needs.

Technical Requirements

Platform support

Windows 10 (x86) with Visual Studio 2019

Ubuntu 18.04 x86_64 with GCC 7

Learn more

Hardware

A RGB video source (minimum 640×480 resolution).

Related Solutions

Affectiva Facial Coding API

Looking to batch videos? Then the Facial Coding API is a cost effective and easy solution where you only pay for the minutes you use.

More about the Affectiva Facial Coding API

Media Analytics

iMotions Lab with Facial Expression Analysis module

Facial Expression Analysis in Research