New landing page

Is your expression a commodity?
​My new portfolio landing page is live at www.oerum.org. It is an interactive "Pattern Recognition Interface" that scans your face in real-time to classify your emotional state.
​Intention:
We often anthropomorphize AI, believing it "sees" or "understands" us. This project strips that illusion away. It presents the algorithm for what it is: a statistical machine measuring surface geometry. The project questions the reduction of complex human affect into rigid taxonomies and highlights the friction between data (the map) and feeling (the territory).
​The Technology:
The interface is built on face-api.js, an open-source library created by Vincent Mühler in 2018 to democratize facial recognition. It runs on top of TensorFlow.js, a machine learning engine developed by the Google Brain team that utilizes the user's GPU directly in the browser.
​The system chains three specific neural networks to function:
​SSD MobileNet V1: A "Single Shot Detector" originally designed for mobile devices, used here to locate the bounding box of the face.
​FaceLandmark68Net: A model trained on labeled datasets to map 68 specific geometric points (jawline, eyes, nose) onto the face.
​FaceExpressionNet: A classifier using Depthwise Separable Convolutions to calculate the statistical probability that these geometric coordinates match a labeled emotion (e.g., "Happy" or "Sad").
​Privacy:
Because this runs on client-side TensorFlow, the surveillance is contained entirely within your own device. No biometric data is sent to the cloud.
​Experience the loop:
www.oerum.org