Real-time system for multi-modal 3D geospatial mapping, object recognition, scene annotation and analytics

Patent metadata

Field	Value
Publication number	US-9488492-B2
Application number	US-201414575472-A
Country	US
Kind code	B2
Filing date	Dec 18, 2014
Priority date	Mar 18, 2014
Publication date	Nov 8, 2016
Grant date	Nov 8, 2016

Abstract

A multi-sensor, multi-modal data collection, analysis, recognition, and visualization platform can be embodied in a navigation capable vehicle. The platform provides an automated tool that can integrate multi-modal sensor data including two-dimensional image data, three-dimensional image data, and motion, location, or orientation data, and create a visual representation of the integrated sensor data, in a live operational environment. An illustrative platform architecture incorporates modular domain-specific business analytics “plug ins” to provide real-time annotation of the visual representation with domain-specific markups.

First claim

The invention claimed is:

1. A navigation-capable vehicle, comprising:
one or more processors, and, in communication with the one or more processors:
one or more two-dimensional image sensors;
one or more sensors to determine motion, location, and orientation of the navigation-capable vehicle; and
one or more non-transitory machine accessible storage media comprising instructions to cause the navigation-capable vehicle to:
temporally and spatially align sensor data received from the one or more two-dimensional image sensors, and the one or more motion, location, and orientation sensors;
generate a map representation of a real world environment in a frame of reference of the navigation-capable vehicle based on the temporally and spatially aligned sensor data;
recognize a plurality of visual features in the map representation using one or more computer vision algorithms;
annotate one or more of the visual features in accordance with domain-specific business logic;

wherein the domain-specific business logic is to cause the navigation-capable vehicle to detect a change in a visual feature of a natural resource.

2. A navigation-capable vehicle, comprising:
one or more processors, and, in communication with the one or more processors:
one or more two-dimensional image sensors;
one or more sensors to determine motion, location, and orientation of the navigation-capable vehicle; and
one or more non-transitory machine accessible storage media comprising instructions to cause the navigation-capable vehicle to:
temporally and spatially align sensor data received from the one or more two-dimensional image sensors, and the one or more motion, location, and orientation sensors;
generate a map representation of a real world environment in a frame of reference of the navigation-capable vehicle based on the temporally and spatially aligned sensor data;
recognize a plurality of visual features in the map representation using one or more computer vision algorithms; and
annotate one or more of the visual features in accordance with domain-specific business logic;

wherein the navigation-capable vehicle comprises an unmanned aerial vehicle.

3. A multi-sensor data collection, analysis, recognition, and visualization platform comprising instructions embodied in one or more non-transitory computer readable storage media and executable by one or more processors to cause a navigation-capable vehicle to:
receive sensor data from a plurality of sensors comprising one or more two-dimensional image sensors, and one or more sensors to determine motion, location, and orientation of the navigation-capable vehicle;
temporally and spatially align the sensor data received from the one or more two-dimensional image sensors, and the one or more motion, location, and orientation sensors;
generate a map representation of the real world surroundings of the navigation-capable vehicle based on the temporally and spatially aligned sensor data;
recognize a plurality of visual features in the map representation by executing one or more computer vision algorithms;
annotate one or more of the visual features in accordance with domain-specific business logic; and
present a visualization of the annotated visual features on the navigation-capable vehicle;

wherein the domain-specific business logic comprises a change detection algorithm to detect one or more domain-specific changes in the visual features over time, and the platform comprises instructions to annotate the visual features to identify the detected domain-specific changes on the visualization.

4. A multi-sensor data collection, analysis, recognition, and visualization platform comprising instructions embodied in one or more non-transitory computer readable storage media and executable by one or more processors to cause a navigation-capable vehicle to:
receive sensor data from a plurality of sensors comprising one or more two-dimensional image sensors, and one or more sensors to determine motion, location, and orientation of the navigation-capable vehicle;
temporally and spatially align the sensor data received from the one or more two-dimensional sensors, and the one or more motion, location, and orientation sensors;
generate a map representation of the real world surroundings of the navigation-capable vehicle based on the temporally and spatially aligned sensor data;
recognize a plurality of visual features in the map representation by executing one or more computer vision algorithms;
annotate one or more of the visual features in accordance with domain-specific business logic; and
present a visualization of the annotated visual features on the navigation-capable vehicle;

wherein the domain-specific business logic comprises an anomaly detection algorithm to detect one or more domain-specific anomalies in the visual features over time, and the platform comprises instructions to annotate the visual features to identify the detected domain-specific anomalies on the visualization.

5. A system for multi-sensor data collection, analysis, recognition, and visualization by a navigation-capable vehicle, the system comprising one or more computing devices configured to:
temporally and spatially align data received from one or more two-dimensional sensors and one or more motion, location, and orientation sensors;
generate a map representation of the real world surroundings of the navigation-capable vehicle based on the temporally and spatially aligned sensor data;
recognize a plurality of visual features in the map representation by executing one or more computer vision algorithms;
estimate a navigation path for the navigation-capable vehicle;
annotate one or more of the visual features in accordance with domain-specific business logic;
present a visualization of the annotated visual features on the navigation-capable vehicle; and
tag one or more of the annotated visual features in the visualization in response to user input.

6. The system of claim 5 , configured to execute domain-specific anomaly detection logic on the visual features and annotate the visualization based on the execution of the domain-specific anomaly detection logic.

7. The system of claim 5 , configured to execute domain-specific change detection logic on the visual features and annotate the visualization based on the execution of the domain-specific change detection logic.

8. The navigation-capable vehicle of claim 2 , wherein one of the one or more two-dimensional image sensors generates two-dimensional image sensor data.

9. The navigation-capable vehicle of claim 2 , wherein one of the one or more two-dimensional image sensors generates three-dimensional image sensor data.

10. The navigation-capable vehicle of claim 2 , further comprising a three-dimensional image sensor.

11. The navigation-capable vehicle of claim 3 , wherein one of the one or more two-dimensional image sensors generates two-dimensional image sensor data.

12. The navigation-capable vehicle of claim 3 , wherein one of the one or more two-dimensional image sensors generates three-dimensional image sensor data.

13. The navigation-capable vehicle of claim 3 , further comprising a three-dimensional image sensor.

14. The navigation-capable vehicle of claim 4 , wherein one of the one or more two-dimensional image sensors generates two-dimensional image sensor data.

15. The navigation-capable vehicle of claim 4 , wherein one of the one or more two-dimensional image sensors generates three-dimensional image sensor data.

16. The navigation-capable vehicle of claim 4 , further comprising a three-dimensi

Assignees

• Stanford Res Inst Int

Inventors

• Samarasekera Supun
• Hadsell Raia
• Kumar Rakesh
• Sawhney Harpreet S
• Matei Bogdan C
• Villamil Ryan

Classifications

• G01C11/02 Primary

  Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures · CPC title

• G06V10/811

  the classifiers operating on different input data, e.g. multi-modal recognition · CPC title

• G06F18/256

  of results relating to different input data, e.g. multimodal recognition · CPC title

• G06F18/24

  Classification techniques · CPC title

• G08G5/70

  Arrangements for monitoring traffic-related situations or conditions · CPC title