CPC G06V 10/454 (2022.01) [G06F 18/2411 (2023.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G06V 30/19173 (2022.01); G06V 40/161 (2022.01); G06V 40/169 (2022.01); G06V 40/172 (2022.01); G06V 40/173 (2022.01)] | 19 Claims |
1. A facial recognition method comprising:
initializing target position and scale within a video frame;
extracting positive and negative face pair samples from candidate face targets in the video frame;
extracting higher-dimensional multi-pixel Haar-like facial features, including pixel intensities, from the positive and negative face pair samples;
using a sparse coding function reducing dimension of the higher-dimensional multi-pixel Haar-like facial features, including:
selecting a sub-set of more discriminative Haar-like facial features from among the higher-dimensional multi-pixel Haar-like facial features; and
forming a sparse feature matrix from the sub-set of more discriminative Haar-like facial features, including:
forming columns linking non-zero items in a solution vector to the sub-set of more discriminative Haar-like facial features; and
deleting columns where the corresponding item in the solution vector is zero; and
classifying targets based on content of the sparse feature matrix.
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