An efficient parallel approach using OpenCL for pupil detection and pupil size measurement

Pupil detection techniques based on video camera are useful for human monitoring and machine-human interface devices. For example, PD can be used in the field of noninvasive intracranial pressure monitor, fatigue detection etc. During the pupil detection process, image pixels can dramatically influence the detection speed, especially when two cameras are used for acquiring images from both left and right eyes. The low detection speed would impact the application for real-time detections. In this paper, in order to improve the detection speed, a parallel pupil detection and pupil size measurement method using the OpenCL (Open Computing Language) framework for the parallel computing was proposed. The experimental results indicated that the proposed method present excellent efficiency than that of CPU-only platforms without compromising the accuracy of pupil detection and pupil size measurement.