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.
