US 12,223,759 B2
Neural network-based recognition of trade workers present on industrial sites
Lai Him Matthew Man, Thornhill (CA); Mohammad Soltani, Toronto (CA); Ahmed Aly, North York (CA); and Walid Aly, North York (CA)
Assigned to Procore Technologies, Inc., Carpinteria, CA (US)
Filed by Procore Technologies, Inc., Carpinteria, CA (US)
Filed on Dec. 29, 2023, as Appl. No. 18/400,592.
Application 18/400,592 is a continuation of application No. 17/959,271, filed on Oct. 3, 2022, granted, now 11,900,708.
Application 17/959,271 is a continuation of application No. 17/010,481, filed on Sep. 2, 2020, granted, now 11,462,042, issued on Oct. 4, 2022.
Application 17/010,481 is a continuation of application No. 16/135,942, filed on Sep. 19, 2018, granted, now 10,769,422, issued on Sep. 8, 2020.
Prior Publication US 2024/0304021 A1, Sep. 12, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06K 9/00 (2022.01); G06F 18/21 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/52 (2022.01); G06V 40/10 (2022.01); G06V 40/20 (2022.01); G06V 10/24 (2022.01)
CPC G06V 40/10 (2022.01) [G06F 18/217 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/52 (2022.01); G06V 40/103 (2022.01); G06V 40/20 (2022.01); G06V 10/245 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A computing platform comprising:
a network interface;
at least one processor;
non-transitory computer-readable medium; and
program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor such that the computing platform is configured to:
receive, via one or more cameras positioned on a construction site, a set of images depicting a particular worker;
based on the set of images, determine a plurality of trade probabilities for the particular worker, each trade probability in the plurality of trade probabilities indicating a likelihood that the particular worker belongs to a particular trade from among a plurality of trades;
extract a set of background datasets from the set of images;
determine, based on the set of background datasets, a set of contextual probabilities, wherein each respective contextual probability of the set of contextual probabilities indicates a likelihood that a respective background dataset of the set of background datasets indicates a trade-specific context from among a plurality of trade-specific contexts;
based on the plurality of trade probabilities and the set of contextual probabilities, select a particular trading having a highest probability; and
determine, based on the highest probability, that the particular worker belongs to the particular trade.