US 11,854,240 B2
Vision based target tracking that distinguishes facial feature targets
Jinjun Wang, San Jose, CA (US); Shun Zhang, Xi'an (CN); and Rui Shi, Xi'an (CN)
Assigned to DeepNorth Inc., Redwood City, CA (US)
Filed by DeepNorth Inc., Foster City, CA (US)
Filed on Dec. 15, 2020, as Appl. No. 17/122,941.
Application 17/122,941 is a division of application No. 15/792,487, filed on Oct. 24, 2017, granted, now 10,902,243.
Claims priority of provisional application 62/412,643, filed on Oct. 25, 2016.
Claims priority of provisional application 62/412,647, filed on Oct. 25, 2016.
Prior Publication US 2021/0142044 A1, May 13, 2021
Int. Cl. G06V 10/44 (2022.01); G06V 40/16 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01); G06V 30/19 (2022.01); G06V 10/764 (2022.01); G06F 18/2411 (2023.01)
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
OG exemplary drawing
 
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.