US 11,887,383 B2
Vehicle interior object management
Panu James Turcot, Pacifica, CA (US); Rana el Kaliouby, Milton, MA (US); Abdelrahman N. Mahmoud, Somerville, MA (US); Mohamed Ezzeldin Abdelmonem Ahmed Mohamed, Cairo (EG); Andrew Todd Zeilman, Beverly, MA (US); and Gabriele Zijderveld, Somerville, MA (US)
Assigned to Affectiva, Inc., Boston, MA (US)
Filed by Affectiva, Inc., Boston, MA (US)
Filed on Aug. 28, 2020, as Appl. No. 17/005,374.
Application 17/005,374 is a continuation in part of application No. 16/833,828, filed on Mar. 30, 2020.
Claims priority of provisional application 62/955,493, filed on Dec. 31, 2019.
Claims priority of provisional application 62/954,833, filed on Dec. 30, 2019.
Claims priority of provisional application 62/954,819, filed on Dec. 30, 2019.
Claims priority of provisional application 62/925,990, filed on Oct. 25, 2019.
Claims priority of provisional application 62/926,009, filed on Oct. 25, 2019.
Claims priority of provisional application 62/893,298, filed on Aug. 29, 2019.
Claims priority of provisional application 62/827,088, filed on Mar. 31, 2019.
Prior Publication US 2020/0394428 A1, Dec. 17, 2020
Int. Cl. G06V 20/59 (2022.01)
CPC G06V 20/59 (2022.01) 29 Claims
OG exemplary drawing
 
1. A computer-implemented method for vehicle management comprising:
collecting two or more images of a vehicle interior using one or more imaging devices within the vehicle;
determining a human perception metric based on the two or more images, wherein the human perception metric includes a cognitive load for an occupant of the vehicle;
analyzing the two or more images to detect an object within the vehicle;
classifying the object within the vehicle;
collecting audio information from within the vehicle;
matching a portion of the audio information to at least one of the two or more images;
estimating a level of interaction between the object and the occupant of the vehicle, wherein the estimating the level of interaction includes calculating an interaction metric and wherein the estimating is also based on the matched portion of the audio information; and
changing a control element of the vehicle based on the classifying and the level of interaction.