This paper describes Sentix AI, a browser-native platform for real-time emotion detection and temporal analytics from video. The system uses Google Gemini's multimodal model to extract per-frame emotional data, catch laugh events, track multiple people, and produce time-coded reports. It runs entirely in the browser with React 19, TypeScript, and the Gemini 1.5 Pro vision API — no GPU, no server, just a web browser and a video file. We tested it across a range of content types, lighting conditions, and face counts. The system introduces an event-based emotion schema that ties together temporal span, peak intensity, and per-person tracking into a single JSON structure. This paper covers the architecture, the trade-offs we made, what breaks in practice, and where we think this can go next — including edge inference, multilingual affect analysis, and clinical use.
Ram.B et al. (Fri,) studied this question.