Identifying Imagery Views Using Geolocated Text

• US 20150371430A1
• Filed: 06/20/2014
• Published: 12/24/2015
• Est. Priority Date: 06/20/2014
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Brewington, Brian Edmond, Shucker, Brian Daniel, Garianov, Alexei
• Application Number:
  US14/310,029
• Publication Number:
  US 20150371430A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 17/05 Geographic models
• CPC Class Codes: G06T 19/20 Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
• CPC Class Codes: G06T 2210/36 Level of detail
• CPC Class Codes: G06T 2219/2016 Rotation, translation, scaling

Abstract

Systems and methods for identifying views for geographic imagery using geolocated text are provided. More specifically, a multi-resolution textual descriptors map associating text with specific geographic locations can be accessed and used to identify a viewpoint for displaying geographic imagery associated with an object of interest. The multi-resolution textual descriptors map can be a collection of data that associates text objects from the geolocated text with a plurality of varying zoom levels relative to the geographic area. The multi-resolution text map can provide labels of varying specificity based on the zoom level relative to the geographic area. Geographic locations and/or zoom levels corresponding to a text object describing or otherwise associated with the object of interest can be identified from the multi-resolution textual descriptors map. A view encompassing the identified geographic locations and/or zoom levels can be used to provide a viewpoint for the object of interest in the imagery.

Claims

1. A computer-implemented method of identifying a viewpoint for displaying geographic imagery, the method comprising:

receiving, by one or more computing devices, data indicative of a request for geographic imagery associated with an object;

accessing, by the one or more computing devices, a multi-resolution textual descriptors map for a geographic area, the multi-resolution textual descriptors map associating geolocated text to one or more geographic locations in the geographic area at a plurality of varying zoom levels relative to the geographic area;

determining, by the one or more computing devices, a viewpoint for displaying geographic imagery associated with the object based at least in part on the multi-resolution textual descriptors map; and

providing, by the one or more computing devices, data for viewing geographic imagery associated with the object from the viewpoint.

2. The computer-implemented method of claim 1, wherein the multi-resolution textual descriptors map associates more specific text objects with more zoomed in levels of the plurality of varying zoom levels of the multi-resolution textual descriptors map.

3. The computer-implemented method of claim 1, wherein the multi-resolution textual descriptors map associates a geolocated text object with one or more of the plurality of varying zoom levels based at least in part on a frequency of the geolocated text object in a geographic area relative to the frequency of the text object in other geographic areas.

4. The computer-implemented method of claim 1, wherein the method comprises identifying a text object associated with the object in the multi-resolution textual descriptors map.

5. The computer-implemented method of claim 4, wherein the viewpoint is determined based at least in part on information associated with the identified text object associated with the object in the multi-resolution textual descriptors map.

6. The computer-implemented method of claim 5, wherein the information comprises a zoom level and geographic position corresponding to the identified text object.

7. The computer-implemented method of claim 1, wherein the multi-resolution textual descriptors map is based on a node tree data structure having a plurality of nodes arranged in a plurality of hierarchical levels in parent-child relationship, each hierarchical level in the node tree data structure corresponding to one of the plurality of zoom levels of the multi-resolution textual descriptors map.

8. The computer-implemented method of claim 7, wherein the node tree data structure is constructed from the geolocated text by associating each occurrence of a geolocated text object with a node corresponding to the geolocation of the text object in the hierarchical level corresponding to the most zoomed in level of the multi-resolution textual descriptors map, and recursively adding the text object to each parent node of the node corresponding to the geolocation of the text object among the plurality of hierarchical levels up to a root node of the node tree data structure.

9. The computer-implemented method of claim 8, wherein the multi-resolution textual descriptors map is generated at least in part by traversing the node tree data structure and generating a relevance score for each text object in a node based at least in part on the frequency of the text object relative to one or more neighboring nodes in the node tree data structure.

10. The computer-implemented method of claim 9, wherein the viewpoint is determined by traversing the node tree data structure to identify a node based at least in part on a relevance score for a text object associated with the object in the multi-resolution textual descriptors map.

11. The computer-implemented method of claim 1, wherein the geolocated text comprises a plurality of text objects extracted from imagery captured of the geographic area by a camera.

12. The computer-implemented method of claim 1, wherein the geolocated text comprises a plurality of text objects associated with business listings in the geographic area.

13. A computing system, comprising:

one or more processors; and

one or more memory devices, the one or more memory devices comprising computer-readable instructions that when executed by the one or more processors cause the one or more processors to perform operations, the operations comprising;

receiving data indicative of a request for geographic imagery associated with an object;

accessing a multi-resolution textual descriptors map for a geographic area, the multi-resolution textual descriptors map associating geolocated text to one or more geographic locations in a geographic area at a plurality of varying zoom levels relative to the geographic area;

determining a viewpoint for displaying geographic imagery associated with the object based at least in part on the multi-resolution textual descriptors map; and

providing data for viewing geographic imagery associated with the object from the viewpoint.

14. The computing system of claim 13, wherein the multi-resolution textual descriptors map associates a geolocated text object with one or more of the plurality of varying zoom levels based at least in part on a frequency of the geolocated text object in a geographic area relative to the frequency of the text object in other geographic areas.

15. The computing system of claim 13, wherein the viewpoint is determined based on information corresponding to a geolocated text object associated with the object in the multi-resolution textual descriptors map.

16. The computing system of claim 15, wherein the viewpoint has a zoom level corresponding to a zoom level associated with the geolocated text object identified in the multi-resolution textual descriptors map.

17. The computing system of claim 16, wherein the zoom level identified in the multi-resolution textual descriptors map encompasses a threshold percentage of geolocated text objects describing the object in the multi-resolution textual descriptors map.

18. One or more tangible, non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations, the operations comprising:

receiving data indicative of a request for geographic imagery associated with a object;

accessing a multi-resolution textual descriptors map for a geographic area, the multi-resolution textual descriptors map associating geolocated text to one or more geographic locations in a geographic area at a plurality of varying zoom levels relative to the geographic area;

determining a viewpoint for displaying geographic imagery associated with the object based at least in part on the multi-resolution textual descriptors map; and

providing data for viewing geographic imagery associated with the object from the viewpoint.

wherein the multi-resolution textual descriptors map is based on a node tree data structure having a plurality of nodes arranged in a plurality of hierarchical levels in parent-child relationship, each hierarchical level in the node tree data structure corresponding to one of the plurality of zoom levels of the multi-resolution textual descriptors map, the node tree data structure is constructed from the geolocated text by associating each occurrence of a geolocated text object with a node corresponding to the geolocation of the text object in the hierarchical level corresponding to the most zoomed in level of the multi-resolution textual descriptors map, and recursively adding the text object to each parent node of the node corresponding to the geolocation of the text object among the plurality of hierarchical levels up to a root node of the node tree data structure.

19. The one or more tangible, non-transitory computer-readable media of claim 18, wherein the multi-resolution textual descriptors map is generated at least in part by traversing the node tree data structure and generating a relevance score for each text object in a node based at least in part on the frequency of the text object relative to one or more neighboring nodes in the node tree data structure.

20. The one or more tangible, non-transitory computer-readable media of claim 18, wherein the viewpoint for displaying the geographic imagery associated with the object is determined based at least in part on the relevance score corresponding to a geolocated text object associated with the object in one or more nodes in the node tree data structure.