Multimodal machine learning for vehicle manipulation
Rana el Kaliouby, Milton, MA (US); Seyedmohammad Mavadati, Watertown, MA (US); Taniya Mishra, New York, NY (US); Timothy Peacock, Concord, MA (US); and Panu James Turcot, Pacifica, CA (US)
Assigned to Affectiva, Inc., Boston, MA (US)
Filed by Affectiva, Inc., Boston, MA (US)
Filed on Apr. 20, 2020, as Appl. No. 16/852,627.
Application 16/852,627 is a continuation in part of application No. 16/127,618, filed on Sep. 11, 2018, granted, now 10,628,741.
Application 16/127,618 is a continuation in part of application No. 15/861,855, filed on Jan. 4, 2018, granted, now 10,204,625, issued on Feb. 12, 2019.
Application 15/861,855 is a continuation in part of application No. 15/670,791, filed on Aug. 7, 2017, granted, now 10,074,024, issued on Sep. 11, 2018.
Application 15/670,791 is a continuation in part of application No. 15/666,048, filed on Aug. 1, 2017.
Application 15/666,048 is a continuation in part of application No. 15/395,750, filed on Dec. 30, 2016, abandoned.
Application 15/395,750 is a continuation in part of application No. 15/262,197, filed on Sep. 12, 2016.
Application 15/262,197 is a continuation in part of application No. 14/796,419, filed on Jul. 10, 2015, abandoned.
Application 14/796,419 is a continuation in part of application No. 14/460,915, filed on Aug. 15, 2014, abandoned.
Application 14/460,915 is a continuation in part of application No. 13/153,745, filed on Jun. 6, 2011, abandoned.
Application 13/153,745 is a continuation in part of application No. 15/875,644, filed on Jan. 19, 2018, granted, now 10,627,817.
Application 15/670,791 is a continuation in part of application No. 14/214,918, filed on Mar. 15, 2014, granted, now 9,723,992, issued on Aug. 8, 2017.
Application 14/214,918 is a continuation in part of application No. 13/153,745, filed on Jun. 6, 2011.
Application 14/214,918 is a continuation in part of application No. 16/852,627.
Application 16/852,627 is a continuation in part of application No. 15/875,644, filed on Jan. 19, 2018.
Application 15/875,644 is a continuation in part of application No. 15/273,765, filed on Sep. 23, 2016.
Application 15/273,765 is a continuation in part of application No. 14/796,419.
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.
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Claims priority of provisional application 62/023,800, filed on Jul. 11, 2014.
Claims priority of provisional application 61/972,314, filed on Mar. 30, 2014.
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Claims priority of provisional application 61/798,731, filed on Mar. 15, 2013.
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Claims priority of provisional application 61/467,209, filed on Mar. 24, 2011.
Claims priority of provisional application 61/447,464, filed on Feb. 28, 2011.
Claims priority of provisional application 61/447,089, filed on Feb. 27, 2011.
Claims priority of provisional application 61/439,913, filed on Feb. 6, 2011.
Claims priority of provisional application 61/414,451, filed on Nov. 17, 2010.
Claims priority of provisional application 61/388,002, filed on Sep. 30, 2010.
Claims priority of provisional application 61/352,166, filed on Jun. 7, 2010.
Prior Publication US 2020/0242383 A1, Jul. 30, 2020
1. A computer-implemented method for machine-trained analysis comprising:
capturing, into a computing device, a plurality of information channels, wherein the plurality of information channels includes contemporaneous audio information and video information from an individual;
learning, on a multilayered convolutional network, trained weights using the audio information and the video information from the plurality of information channels, wherein the trained weights are trained from both the audio information and the video information and are trained simultaneously, and wherein the learning facilitates cognitive state analysis of the audio information and the video information;
capturing, within a vehicle, further information and analyzing the further information using the trained weights; and
manipulating the vehicle, based on the analyzing the further information, and wherein the analyzing of the further information further comprises counting occurrences of a specific emotion type.
