US 11,987,272 B2
System and method of predicting human interaction with vehicles
Samuel English Anthony, Cambridge, MA (US); Kshitij Misra, Cambridge, MA (US); and Avery Wagner Faller, Cambridge, MA (US)
Assigned to Perceptive Automata, Inc., Cambridge, MA (US)
Filed by Perceptive Automata, Inc., Boston, MA (US)
Filed on Mar. 3, 2021, as Appl. No. 17/190,619.
Application 17/190,619 is a continuation in part of application No. 16/828,823, filed on Mar. 24, 2020, granted, now 11,126,889.
Application 16/828,823 is a continuation of application No. 16/512,560, filed on Jul. 16, 2019, granted, now 10,614,344, issued on Apr. 7, 2020.
Application 16/512,560 is a continuation of application No. 15/830,549, filed on Dec. 4, 2017, granted, now 10,402,687, issued on Sep. 3, 2019.
Claims priority of provisional application 62/528,771, filed on Jul. 5, 2017.
Prior Publication US 2021/0182604 A1, Jun. 17, 2021
Int. Cl. G06N 3/08 (2023.01); B60W 30/00 (2006.01); B60W 60/00 (2020.01); G05D 1/00 (2006.01); G06F 18/214 (2023.01); G06F 18/40 (2023.01); G06N 3/04 (2023.01); G06N 3/084 (2023.01); G06V 10/778 (2022.01); G06V 20/40 (2022.01); G06V 20/58 (2022.01); G06V 40/20 (2022.01); G08G 1/04 (2006.01); G08G 1/16 (2006.01); G06N 5/01 (2023.01); G06N 20/10 (2019.01); G06V 10/62 (2022.01)
CPC B60W 60/00274 (2020.02) [B60W 30/00 (2013.01); G05D 1/0088 (2013.01); G06F 18/214 (2023.01); G06F 18/41 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06N 3/084 (2013.01); G06V 10/7784 (2022.01); G06V 20/41 (2022.01); G06V 20/58 (2022.01); G06V 40/20 (2022.01); G08G 1/04 (2013.01); G08G 1/166 (2013.01); G05D 2201/0213 (2013.01); G06N 5/01 (2023.01); G06N 20/10 (2019.01); G06V 10/62 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving a plurality of training images of an environment, the plurality of training images including one or more persons;
sending the plurality of training images to annotators via a user interface requesting user responses describing an attribute of the one or more persons;
for the plurality of training images, receiving a plurality of user responses from the annotators, each user response describing the attribute of the one or more persons displayed in the plurality of training images;
generating a training dataset comprising summary statistics of the plurality of user responses describing the attribute of the one or more persons displayed in the plurality of training images;
training, using the training dataset, a machine learning based model configured to receive input images and predict summary statistics describing an attribute of one or more persons displayed in the input images;
receiving a plurality of new images of a new environment, the plurality of new images including one or more new persons;
predicting, using the machine learning based model, summary statistics describing an attribute of the one or more new persons in the plurality of new images; and
determining an action to be performed based on the predicted summary statistics of the one or more new persons.