Recently, eye-tracking techniques are widely used in several fields. In clinical applications, an accurate and reliable eye tracking is of great value. For example, the detection and analysis of eye movement can show valuable indications of a large number of ophthalmic diseases, such as facial nerve paralysis, which is a very common problem in western countries; an accurate eye tracking can also serve as an additional means of communication and interaction when the ophthalmologists’ hands and feet are heavily constrained by other medical devices during their operations.
In most clinics, the eye tracking systems are not cost-effective and require specialists to operate. It is also very difficult to utilise the existing eye tracking systems in the diagnosis of children due to their lack of sustainable attentions.
The purpose of this project is to build a framework to allow automatic tracking of eye movement through multiple platforms including mobile video cameras. Such a framework has great potential in many applications. In clinical applications, this can be used for self examination of eye movement of patients using moderate devices such as mobile phones. Such a self examination can largely reduce the healthcare cost. Moreover, we also anticipate that the eye tracking techniques have great potential in other applications, such as human computer interaction, attention detection, etc. As we are targeting moderate devices, which are widely possessed by the public nowadays, we expect a high level of applicability and great interest from many potential users