1. Making stand-alone PS-OG technology tolerant to the equipment shifts
- Author
-
Oleg V. Komogortsev and Raimondas Zemblys
- Subjects
Artificial neural network ,Computer science ,010401 analytical chemistry ,Real-time computing ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,020207 software engineering ,02 engineering and technology ,Image processing software ,Virtual reality ,Perceptron ,01 natural sciences ,Gaze ,0104 chemical sciences ,Rendering (computer graphics) ,Power consumption ,0202 electrical engineering, electronic engineering, information engineering - Abstract
Tracking users' gaze in virtual reality headsets allows natural and intuitive interaction with virtual avatars and virtual objects. Moreover, a technique known as foveated rendering can help save computational resources and enable hi-resolution but lightweight virtual reality technologies. Predominantly, eye-tracking hardware in modern VR headsets consist of infrared camera(s) and LEDs. Such hardware, together with image processing software consumes a substantial amount of energy, and, provided that hi-speed gaze detection is needed, might be very expensive. A promising technique to overcome these issues is photo-sensor oculography (PS-OG), which allows eye-tracking with high sampling rate and low power consumption. However, the main limitation of the previous PS-OG systems is their inability to compensate for the equipment shifts. In this study, we employ a simple multi-layer perceptron neural network to map raw sensor data to gaze locations and report its performance for shift compensation. Modeling and evaluation is done via a simulation.
- Published
- 2018