公开(公告)号：US10289938B1

公开(公告)日：2019-05-14

申请号：US15596155

申请日：2017-05-16

Applicant: State Farm Mutual Automobile Insurance Company

Inventor： Elizabeth Flowers ,  Puneit Dua ,  Eric Balota ,  Shanna L. Phillips

IPC: G06K9/00 ,  G06K9/62

Abstract: Systems and methods are described for generating an image-based prediction model, where a computing device may obtain a set 3D images from a 3D image data source. Each of the 3D images can have 3D point cloud data and a Distification technique can be applied to the 3D point cloud data of each 3D image to generate output feature vector(s). The output feature vector(s) may then be used to train and generate the image-based prediction model.

公开(公告)号：US10262226B1

公开(公告)日：2019-04-16

申请号：US15596189

申请日：2017-05-16

Applicant: State Farm Mutual Automobile Insurance Company

Inventor： Elizabeth Flowers ,  Puneit Dua ,  Eric Balota ,  Shanna L. Phillips

IPC: G06K9/00 ,  G06K9/42 ,  G06K9/62

Abstract: Systems and methods are described for generating an enhanced prediction from a 2D and 3D image-based ensemble model. In various embodiments, a computing device can be configured to obtain one or more sets of 2D and 3D images and to standardize each of the 2D and 3D images to allow for comparison and interoperability. Corresponding 2D3D image pairs can be determined from the standardized 2D and 3D pairs where the 2D and 3D images correspond based on a common attribute, such as a similar timestamp or time value. The enhanced prediction can use separate underlying 2D and 3D prediction models where the 2D and 3D images of a 2D3D pair are each input to the respective underlying 2D and 3D prediction models to generate respective 2D and 3D predict actions.