3D Object Positioning Using Depth Data for Accurate Geolocation
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Solution Overview
Problem
Geographical information systems often provide inaccurate location data, particularly when a business is located in a building with an entrance on an adjacent street, leading to incorrect placement of objects on maps and images.
Innovation Solution
The system corrects the placement of objects on maps and images by using depth data from three-dimensional scenes to translate coordinates from a two-dimensional image to geolocated coordinates, ensuring accurate positioning by constraining objects to the façade of structures and using depth values to determine precise locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If location data is obtained from standard geographical information systems, then location information is provided quickly and easily, but the accuracy of the location data deteriorates when businesses are located in buildings with entrances on adjacent streets
Solution Approach 1:
The patent uses depth data as an intermediary to bridge the gap between 2D image coordinates and accurate 3D geolocations. The depth information acts as a mediator that translates imprecise map coordinates into accurate real-world locations by accounting for the three-dimensional structure of buildings and their façades.
Solution Approach 2:
The patent transitions from two-dimensional map coordinates to three-dimensional geolocations by incorporating depth data. This dimensional enhancement allows the system to resolve ambiguities in 2D space by adding the depth dimension, enabling precise identification of building entrances and façades.
2Productivity
If objects are placed on two-dimensional map images using standard coordinate systems, then placement is simple and fast, but the precision of object positioning deteriorates when the same coordinates correspond to multiple locations on building façades
Solution Approach 1:
The patent resolves the ambiguity of 2D coordinates mapping to multiple 3D locations by introducing depth as an additional dimension. This allows the system to distinguish between different façades and entrances that share the same 2D coordinates, enabling precise object placement at the correct building entrance.
Solution Approach 2:
The patent applies different processing approaches to different regions of the image based on depth data. By identifying which portions of the image correspond to building façades versus other features, the system can apply localized coordinate transformations that preserve precision for building-related objects while maintaining overall processing efficiency.
3Measurement precision
If depth data is incorporated to improve location accuracy, then positioning precision is improved, but the complexity of the system increases due to additional data processing requirements
Solution Approach 1:
The patent uses depth data as a mediating layer that simplifies the overall complexity by providing a straightforward translation mechanism between 2D and 3D coordinates. Rather than implementing complex 3D reconstruction algorithms, the system leverages pre-computed depth information to achieve accurate positioning with relatively simple coordinate transformation logic.
Data Source
AI summary
Systems, methods, and computer storage mediums are provided for correcting the placement of an object on an image. An example method includes providing the image and depth data that describes the depth of the three-dimensional scene captured by the image. The depth data describes at least a distance between a camera that captured the three-dimensional scene and one or more structures in the scene and a geolocation of the camera when the three-dimensional scene was captured. When the object is moved from a first location on the image to a second location on the image, a set of coordinates that describes the second location relative to the image is received. The set of coordinates are then translated into geolocated coordinates that describe a geolocation that corresponds to the second location. The set of coordinate is translated, at least in part, using the depth data associated with the image.