Science Based – 3D Geometrical Eye Model
The 3D eye model is a representation of the human eye that takes into account the anatomy and physiology of the human eye. It consists of two main elements: an eyeball and an iris. The eyeball is represented by a sphere with some additional information about its position and orientation in space, while the iris is represented by a disc with some additional information about its position and orientation in space.
Using a 3D eye model, synthetic images from any point of view (POV) can be used to create synthetic training data for deep learning models. The advantage of our approach is that it allows us to automatically detect eyes in any pose and any angle with high accuracy while maintaining compatibility with existing eye tracking systems that have been designed for non-invasive measurements.
Reduced Bias – Large Scale Synthetic Eye Databases
In recent years, there has been a surge of interest in the use of deep learning methods to classify eyes. While these techniques have shown great promise, they are often limited by their inability to adapt to new subjects and contexts. This problem is particularly pronounced when the classifier is applied to new age groups or ethnicities. The problem is further complicated by the fact that eye appearance can be significantly altered by specific medical conditions causing asymmetrical behavior. For example, wall-eyes, lazy-eye, or cross-eyed.
NVISO overcomes this these problems, by using very large scale databases of eye images that have been annotated with a large number of key points, gaze, and eye openness. These databases allow us to train models that are robust across different ages, genders, and ethnicities, while still maintaining high accuracy on a single individual and work independently on the left and right eye.
Digital avatars are computer-generated images or animations that represent a real person, such as an actor or celebrity. Eye tracking can be used in digital avatars to make them more human by mimicking the way people interact with each other and the environment. When an avatar looks at something, we expect it to focus on that object and not wander off too quickly. When their eyes roam around the room, they should track back and forth, not stop abruptly.
Eye tracking is important for creating realistic digital avatars because eye tracking methods can be used to interpret the user’s intention and emotional state: gazing, blinking and eye openness. NVISO eye tracking on software can be used to precisely detect the eye movements of a user and then animate their face accordingly using artificial intelligence algorithms. This allows digital avatars to be more lifelike than ever before!