Vehicle identification driven by augmented reality (AR)
US-10699323-B1 · Jun 30, 2020 · US
US11636526B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11636526-B2 |
| Application number | US-202016946549-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 26, 2020 |
| Priority date | Aug 21, 2019 |
| Publication date | Apr 25, 2023 |
| Grant date | Apr 25, 2023 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A device receives user rendering data for a 3-D rendering of a user. The 3-D rendering is a proportional representation of the user and the user rendering data is available via an application. The device determines user characteristics of the user. The device receives an indication that a user device has submitted a vehicle search request. The device identifies vehicles to recommend to the user based on an analysis of: the user characteristics, and vehicle characteristics for a collection of vehicles being offered via the application. The device causes vehicle description data for the vehicles to be displayed via an interface of the application. The device receives user interaction data that indicates a user selection of vehicle. The device causes, based on receiving the user interaction data, the interface of the application to display a placement of the 3-D rendering of the user into a 3-D rendering of the vehicle.
Opening claim text (preview).
What is claimed is: 1. A method, comprising: receiving, by a device, user rendering data for a three-dimensional (3-D) rendering of a user, wherein the 3-D rendering of the user is a proportional representation of the user; determining, by the device and by processing the user rendering data, a set of user characteristics of the user, wherein the set of user characteristics includes at least one of: a height of the user, a width of one or more body parts of the user, or a length of the one or more body parts of the user; identifying, by the device, a set of vehicles to recommend to the user based on a machine learning driven analysis of: the set of user characteristics, and a set of vehicle characteristics for a collection of vehicles, wherein the set of vehicle characteristics includes at least one of: a first seat placement characteristic, that is associated with a minimum seat extension distance, for one or more seats included within the collection of vehicles, a second seat placement characteristic, that is associated with a maximum seat extension distance, for the one or more seats included in the collection of vehicles, or a distance between a first point of the one or more seats and a second point of one or more ceilings of one or more vehicles included in the collection of vehicles; and causing, by the device, display of a placement of the 3-D rendering of the user in a 3-D rendering of a particular vehicle of the set of vehicles. 2. The method of claim 1 , further comprising: causing, while causing display of the placement of the 3-D rendering of the user, display of a score that indicates a likelihood of the particular vehicle being compatible with the user, the likelihood of the particular vehicle being compatible with the user being based on the set of user characteristics and the set of vehicle characteristics. 3. The method of claim 1 , further comprising: providing, to a user device associated with the user, data that causes the user device to display the set of vehicles via an application operating on the user device; and receiving, from the user device and based on a user selection made using the application, data identifying the particular vehicle; and wherein causing display of the placement of the 3-D rendering of the user comprises: causing display of the placement of the 3-D rendering of the user based on receiving the data identifying the particular vehicle. 4. The method of claim 1 , further comprising: receiving in-vehicle object data for a three-dimensional (3-D) rendering of an in-vehicle object; and causing display of a placement of the 3-D rendering of the in-vehicle object in the 3-D rendering of the particular vehicle. 5. The method of claim 1 , further comprising: generating the 3-D rendering of the particular vehicle based on the set of vehicle characteristics. 6. The method of claim 1 , further comprising: generating a plurality of 3-D renderings of the particular vehicle based on the set of vehicle characteristics, the plurality of 3-D renderings of the particular vehicle being associated with different seat placement characteristics; and selecting the 3-D rendering of the particular vehicle, from the plurality of 3-D renderings of the particular vehicle, based on the set of user characteristics. 7. The method of claim 1 , further comprising: generating the 3-D rendering of the user based on the user rendering data. 8. A device, comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: receive user rendering data for a three-dimensional (3-D) rendering of a user, wherein the 3-D rendering of the user is a proportional representation of the user; determine, by processing the user rendering data, a set of user characteristics of the user, wherein the set of user characteristics includes at least one of: a height of the user, a width of one or more body parts of the user, or a length of the one or more body parts of the user; identify a set of vehicles to recommend to the user based on a machine learning driven analysis of: the set of user characteristics, and a set of vehicle characteristics for a collection of vehicles, wherein the set of vehicle characteristics includes at least one of: a first seat placement characteristic, that is associated with a minimum seat extension distance, for one or more seats included within the collection of vehicles, a second seat placement characteristic, that is associated with a maximum seat extension distance, for the one or more seats included in the collection of vehicles, or a distance between a first point of the one or more seats and a second point of one or more ceilings of one or more vehicles included in the collection of vehicles; and cause display of a placement of the 3-D rendering of the user in a 3-D rendering of a particular vehicle of the set of vehicles. 9. The device of claim 8 , wherein the one or more processors are further configured to: cause, while causing display of the placement of the 3-D rendering of the user, display of a score that indicates a likelihood of the particular vehicle being compatible with the user, the likelihood of the particular vehicle being compatible with the user being based on the set of user characteristics and the set of vehicle characteristics. 10. The device of claim 8 , wherein the one or more processors are further configured to: provide, to a user device associated with the user, data that causes the user device to display the set of vehicles via an application operating on the user device; and receive, from the user device and based on a user selection made using the application, data identifying the particular vehicle; and wherein the one or more processors, when causing display of the placement of the 3-D rendering of the user, are configured to: cause display of the placement of the 3-D rendering of the user based on receiving the data identifying the particular vehicle. 11. The device of claim 8 , wherein the one or more processors are further configured to: receive in-vehicle object data for a three-dimensional (3-D) rendering of an in-vehicle object; and cause display of a placement of the 3-D rendering of the in-vehicle object in the 3-D rendering of the particular vehicle. 12. The device of claim 8 , wherein the one or more processors are further configured to: generate the 3-D rendering of the particular vehicle based on the set of vehicle characteristics. 13. The device of claim 8 , wherein the one or more processors are further configured to: generate a plurality of 3-D renderings of the particular vehicle based on the set of vehicle characteristics, the plurality of 3-D renderings of the particular vehicle being associated with different seat placement characteristics; and select the 3-D rendering of the particular vehicle, from the plurality of 3-D renderings of the particular vehicle, based on the set of user characteristics. 14. The device of claim 8 , wherein the one or more processors are further configured to: generate the 3-D rendering of the user based on the user rendering data. 15. A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to: receive user rendering data for a three-dimensional (3-D) rendering of a user, wherein the 3-D rendering of the user is a proportional representation of the user; determine, by processing the user
graphically representing goods, e.g. 3D product representation · CPC title
Mixed reality (object pose determination, tracking or camera calibration for mixed reality G06T7/00) · CPC title
Three-dimensional [3D] image rendering · CPC title
Recommending goods or services · CPC title
by specifying product or service characteristics, e.g. product dimensions · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.