360-Degree Photo Pose Estimation Using Visual Place Annotations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing panoramic image technologies face inaccuracies in location and orientation data due to interference from factors like magnetic field distortions and poor GPS signal reception, leading to imprecise pose data for 360-degree spherical or cylindrical panoramas.
Innovation Solution
The method involves receiving an image and associated pose data, determining places with known locations, annotating these places within the image, and minimizing the difference between annotations and their respective known locations to obtain updated pose data, which includes adjusting the image's orientation and location to align projections with their known coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If device sensors (compass, GPS, accelerometer) are used to capture pose data, then the capturing process is simple and quick, but the location and orientation accuracy deteriorates due to magnetic field distortions and poor GPS signal
Solution Approach 1:
The patent introduces an intermediary optimization process that uses visual place recognition and geometric constraints as a mediator between the raw sensor data and the final pose estimation. Instead of directly trusting sensor readings, the system uses detected places and their spatial relationships as an intermediary to correct and refine the pose data, resolving the contradiction between quick capturing and accurate measurement.
Solution Approach 2:
The system implements feedback by using the detected places and their known locations to evaluate and correct the initial pose estimation. The optimization process continuously refines the pose data by comparing it against the geometric constraints derived from place locations, creating a feedback loop that improves accuracy while maintaining the efficiency of the initial sensor-based capture.
2Loss of time
If sensor readings are used directly for pose data, then the processing time is minimal, but the reliability of location and orientation information deteriorates due to environmental interference
Solution Approach 1:
The patent applies preliminary action by performing place detection and location matching before final pose optimization. The system pre-identifies places in the image and retrieves their known locations, preparing geometric constraints in advance. This preliminary processing enables faster and more reliable final optimization by having the constraint information ready before the refinement stage.
3Measurement precision
If compass calibration is performed frequently to maintain accuracy, then the orientation precision improves, but the ease of operation deteriorates due to additional calibration steps required
Solution Approach 1:
The system applies self-service by automatically performing pose optimization using geometric constraints from detected places without requiring manual user intervention for calibration. The algorithm autonomously refines the orientation data by comparing sensor readings against the spatial relationships of identified places, eliminating the need for users to perform repetitive calibration steps while maintaining high precision.
Data Source
AI summary
This technology relates to optimizing location and orientation information of an image using known locations of places captured within the image. For example, an image and associated pose data including the image's orientation and location may be received. One or more places captured within the image may be determined, with each place having a respective known location. The image may be annotated with the one or more places. A difference between each annotation and its respective known location to obtain updated pose data of the image may be minimized and the associated pose data may be updated to the updated pose data.