Year: 2004
Type: preprint
Abstract: Gaze detection and head orientation are an important part of many advanced human-machine interaction applications. Many systems have been proposed for gaze detection. Typically, they require some form of user cooperation and calibration. Additionally, they may require multiple cameras and/or restricted head positions. We present a new approach for inference of both face orientation and gaze direction from a single image with no restrictions on the head position. Our algorithm is based on a face and eye model, deduced from anthropometric data. This approach allows us to use a single camera and requires no cooperation from the user. Using a single image avoids the complexities associated with of a multi-camera system. Evaluation tests show that our system is accurate, fast and can be used in a variety of applications, including ones where the user is unaware of the system.
Source: arXiv (Cornell University)
Authors: Kaminski, J. Y., Teicher, M., Knaan, D., Shavit, A.
Institution: Bar-Ilan University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W31885036