Abstract
In order to obtain eye features for line-of-sight tracking, a pupil detection method with high real-time performance and accuracy was proposed. Real-time performance was improved by cropping the redundant edge image with template matching to locate the position of the eye in the image, and reducing the amount of pupil detection calculations. The shape and color of the pupil and the rules of eye movement were used to obtain the distribution rule of the pupil in the image. The distribution rule was excluded to improve the accuracy of pupil detection. The experimental results show that on the NVIDIA Jetson TX2 embedded computer, the detection accuracy of the pupil detection method reaches 95.06%, the detection rate is 95 fps, and the time-consuming average reduction is 55.33%, which has good practicality.
| Translated title of the contribution | Image Cropping and Abnormal Pupil Exclusion for Pupil Detection |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1111-1118 |
| Number of pages | 8 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 40 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 1 Oct 2020 |