Real-time video analysis for the web
For multiple use cases like face filters, object detection and tracking, emotion detection...
We have developed a deep learning engine able to analyze a video stream in real-time in the web browser. It brings advanced computer vision to web applications. Then augmented reality becomes possible in a web context.
We have created a framework around our deep learning engine to generate training samples, instantiate neural networks, train them, run neuron networks and build applications. It is a highly optimized end-to-end system.
Write once, run everywhere
Our computer vision framework only relies on open and standardized technologies like WebGL or WebRTC. Thus it works everywhere: on websites (in the web browser), on mobile applications (Progressive Web Applications), on desktop applications (with Electron) and even on embedded hardware (using Nvidia Jetson).
We are flexible
We can create and train outstanding artificial neural networks to solve any kind of real-time computer vision problems.
Our first demonstration is a glasses virtual tryon web application. You can check it on jeeliz.com/sunglasses. It was released at the beginning of 2016 and it was the first web application implementing deep learning in the browser matching a commercial use-case.
In this example, the neural network inputs an image and outputs whether it is a face or not, what are the position and the rotation of the face, and even lighting parameters. Then the glasses 3D model is rendered over the video at the right place and orientation and coherently enlighted. This process is repeated dozens of times per second, more than once per new video frame. Thus the virtual glasses follow the head smoothly and accurately.
We bet on the GPU
Our deep learning engine runs on the graphic processing unit (GPU). Nowadays even the cheapest mobile phones have a dedicated GPU. The GPU is better than the CPU for parallel computing. GPUs are less impacted by the Moore’s law than CPU’s because they can scale horizontally. So their computing power is still increasing consequently.
What makes the difference?
Read more: Why is our technology unique?