Mobile Navigation Image Matching via Pose and Motion Metadata
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Solution Overview
Problem
Mobile devices have limited displays and a user's limited attention while navigating, making it difficult to select and display the most effective images from a large database to aid navigation, especially when distinguishing between camera motion and scene motion.
Innovation Solution
The system uses user pose estimation and camera orientation to match user location and motion with the corresponding images in a database, selecting images based on metadata such as location, orientation, and motion, and providing modes like stationary, interpolation, and extrapolation to assist navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large database of images is used to support navigation, then the completeness and coverage of navigation information is improved, but the difficulty of selecting and displaying the most effective images increases
Solution Approach 1:
The patent applies parameter changes by using metadata parameters (location, orientation, motion) to characterize and filter images in the database. By changing the selection criteria from manual review to automated parameter matching, the system can efficiently manage large image databases while maintaining ease of operation.
Solution Approach 2:
The system implements self-service by automatically selecting and displaying relevant images based on user context (location, pose, motion) without requiring manual intervention. The navigation system serves itself by autonomously querying the image database and presenting appropriate visual information.
2Measurement precision
If image selection is based on detailed camera motion analysis, then the precision of image matching is improved, but the difficulty of detecting and measuring camera motion increases
Solution Approach 1:
The patent uses an intermediary approach by introducing metadata as a mediator between camera motion capture and image selection. Instead of directly analyzing complex camera motion, the system uses intermediate metadata parameters (orientation, location, motion type) that are easier to detect and measure, while still enabling precise image matching.
3Adaptability or versatility
If the system provides multiple navigation modes (stationary, interpolation, extrapolation), then the adaptability of the navigation system is improved, but the device complexity increases
Solution Approach 1:
The patent applies dynamics by making the navigation system adaptable and flexible through multiple operational modes. The system can dynamically switch between stationary, interpolation, and extrapolation modes based on user needs, allowing it to adapt to different navigation scenarios while maintaining a relatively simple underlying architecture.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient retrieval and display of relevant images on mobile devices, enhancing user navigation by matching user pose and motion with captured images, thereby improving orientation and route planning with minimal user interaction.
Implementation Method 1
an accelerometer for detecting mobile device acceleration; a processor for deriving user pose from the mobile device acceleration
Data Source
AI summary
Method, apparatus and system for improving navigation using mobile devices by adding previously captured media to navigation maps provided by mobile device. Added media include still images and video clips. Media captured at the same location using various camera orientations are available in an image database. Images in database include metadata indicating location, orientation and other parameters associated with each image. User location and pose are matched against metadata indicating location and camera orientation of captured images. User motion may also be matched to metadata indicating camera motion of stored video clips. Other parameters like lighting, seasonal factors, and tasks of walking, biking or driving may also be matched. User pose may be derived from an accelerometer embedded in the mobile device. Some or all of user parameters desired by user may be directly input to mobile device by user instead of being automatically detected by mobile device.