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Systems and methods for 3D image distification

專利號(hào)
US11176414B1
公開日期
2021-11-16
申請(qǐng)人
STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY（US IL Bloomington）
發(fā)明人
Elizabeth Flowers; Puneit Dua; Eric Balota; Shanna L. Phillips
IPC分類
G06K9/62; G06K9/42; G06K9/00
技術(shù)領(lǐng)域
3d,2d,image,images,or,computing,matrix,in,2d3d,model
地域： IL IL Bloomington

摘要

Systems and methods are described for Distification of 3D imagery. A computing device may obtain a three dimensional (3D) image that includes rules defining a 3D point cloud used to generate a two dimensional (2D) image matrix. The 2D image matrix may include 2D matrix point(s) mapped to the 3D image, where each 2D matrix point can be associated with a horizontal coordinate and a vertical coordinate. The computing device can generate an output feature vector that includes, for at least one of the 2D matrix points, the horizontal coordinate and the vertical coordinate of the 2D matrix point, and a depth coordinate of a 3D point in the 3D point cloud of the 3D image. The 3D point can have a nearest horizontal and vertical coordinate pair that corresponds to the horizontal and vertical coordinates of the at least one 2D matrix point.

說(shuō)明書

For example, in the automobile insurance industry, a risk factor can be determined based on driver activity or behavior, such as, for example, gesture detection. Driver behavior can be categorized into distracted or unsafe driving behavior, such as, for example, using a phone while driving, texting while driving, and eating or drinking while driving. Driver behavior can also be categorized into normal or safe driving behavior, such as, for example, when the driver has two hands on the steering wheel, has eyes forward, or is otherwise operating the vehicle in a non-distracted manner. In certain embodiments disclosed herein, a risk factor for a given driver can be determined based on the identified driver behaviors for that driver. The risk factor may be developed over a given period of time, such as based on a single trip from a first location to a second location or based on multiple trips that indicate certain history or pattern of behavior.

In certain embodiments, driver behavior may be identified by any number of computing devices, such as the computing devices described for FIGS. 1 and 2. FIG. 6A shows an embodiment of computing devices mounted within a vehicle for image capture. The embodiment of FIG. 6A depicts two computing devices 604 and 606 mounted above the dashboard 602 in the interior of a vehicle. In FIG. 6A, computing device 604 can be a webcam that takes 2D images and computing device 606 can be a 3D sensor. In other embodiments, as describe herein, a single computing device may be used that can capture both 2D and 3D images. Such a device may be, in some embodiments, hidden or otherwise mounted inside the dashboard or other area of the vehicle.

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