Detection capability
Eye Tracking Analysis
Gaze behaviour, fixation, and pupil response are analysed as visible signals of emotional state, with changes in eye movement and gaze patterns considered over time.
Eye Tracking Emotion Analysis analyses gaze behaviour, fixation, and pupil response to identify visible cues associated with emotional states. The capability considers changes in how a person looks, focuses, and moves their eyes rather than relying only on a single still frame. Different emotional states can be reflected through different gaze and pupil patterns. Happiness can appear through steady focus and dilated pupils. Anger can be associated with piercing stares and fewer blinks, while sadness can appear through a downward gaze and slower blinking. Surprise can be reflected through rapid pupil shifts. Fear can appear through erratic gaze patterns and quick, frequent blinks. By considering these visible eye and gaze patterns, Eye Tracking Analysis provides an additional signal for understanding emotional state within the wider multimodal platform.
Deepfake Detection is one of eight signals used by the Trust Factor Engine. It is considered alongside the other seven signals rather than being treated as the only basis for the overall result. The engine considers multiple signals together when assessing whether the video, voice, or face being evaluated can be trusted. A single signal does not independently determine the final verdict. How the weighting works
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Capabilities are components. The platform page shows how the eight combine into one score.
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