Learned Human Eye Gaze for Object Tracking: A Preliminary Study
Yejie Jiang, Binhui Jiang, Clifford C. Chou · SAE International Journal of Transportation Safety · 2025
Visual object tracking technology is the core foundation of intelligent driving, video surveillance, human–computer interaction, and the like. Inspired by the mechanism of human eye gaze, a new correlation filter (CF) tracking algorithm, named human eye gaze (HEG) tracking algorithm, was proposed in this study. The HEG tracking algorithm expanded the tracking detection idea from the traditional detection-tracking to detection-judging-tracking by adding a judging module to check the initial and retrack the unreliable tracking result. In addition, the detection module was further integrated into the edge contour feature on the basis of the HOG (histogram of oriented gradients) extracting feature and the color histogram to reduce the sensitivity of the algorithm to factors such as deformation and illumination changes. The comparison conducted on the OTB-2015 dataset showed that the overall overlap precision, distance precision, and center location error of the HEG tracking algorithm were significantly better than those of nine transitional mainstream tracking algorithms. Even in the challenging sequences, the HEG tracking algorithm on handling of occlusion, out-of-view, deformation, and illumination variations are obviously advantageous.