A New Human Eye Tracking Method Based on Tracking Module Feedback TLD Algorithm

Existing human eye tracking research is based on the off-line sample training cascade classifier and the traditional tracking algorithm. However, it is difficult to adapt to situations where human eye is partially blocked, gets morphological changes or scale changes and so on. In order to solve these problems, the tracking-learning-detection algorithm for online single-target long-term tracking is used and improved. A novel eye tracking method—the human eye tracking-learning-detection algorithm with tracking feedback is proposed. The detection area is adjusted adaptively and narrowed by the tracking feedback. Above problems are solved, the interference of similar targets is avoided, and the speed of human eye tracking is enhanced. The experimental results show that the algorithm has high tracking accuracy and frames per second.

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