Accelerometer-Based AR Information Extraction
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Solution Overview
Problem
Current methods for obtaining augmented reality (AR) information from image capture devices are overly complex and resource-intensive, often resulting in inaccurate results and unnecessary resource utilization due to the need for complex calculations and continuous transmission of video frames.
Innovation Solution
The method involves detecting a low acceleration condition using sensors like accelerometers to selectively extract and analyze data from video frames, reducing the need for continuous data transmission and processing, and using this data to obtain and implement AR information efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video frames are transmitted continuously for analysis, then AR information can be obtained, but resource utilization (processor, power, bandwidth) increases unnecessarily
Solution Approach 1:
The system transitions from continuous frame transmission to periodic sampling based on acceleration conditions. During low acceleration conditions, frames are transmitted at regular intervals; during high acceleration conditions, transmission is suspended. This periodic action reduces resource utilization while maintaining AR information accuracy by analyzing only relevant frames.
Solution Approach 2:
The system changes the transmission parameter (frame rate) based on the acceleration condition parameter. When acceleration is below the threshold, frames are transmitted at normal intervals; when acceleration exceeds the threshold, transmission pauses. This dynamic parameter adjustment optimizes resource utilization while maintaining analysis accuracy.
2Reliability
If motion vectors are calculated to discover differences between successive frames, then AR information can be obtained, but the process becomes overly complex
Solution Approach 1:
The system extracts only the essential information needed for AR analysis from video frames, rather than performing complete motion vector calculations on all frames. By selecting frames based on acceleration conditions and extracting only relevant features, the system reduces processing complexity while maintaining AR information accuracy.
Solution Approach 2:
Instead of analyzing every frame completely, the system performs partial analysis on selectively chosen frames. This partial action approach reduces computational complexity while still obtaining sufficient AR information, avoiding the excessive processing required for full frame-by-frame motion vector calculation.
3Reliability
If every frame of the video is transmitted for analysis, then complete AR information can be obtained, but bandwidth utilization increases unnecessarily
Solution Approach 1:
The system implements periodic frame transmission based on acceleration conditions rather than continuous transmission. During low acceleration periods, frames are transmitted at intervals; during high acceleration periods, transmission pauses. This reduces bandwidth utilization while maintaining AR information completeness by ensuring relevant frames are still analyzed.
Solution Approach 2:
The system extracts and transmits only the necessary frames for AR analysis rather than every frame. By selecting frames based on acceleration thresholds and identifying which frames contain relevant information, the system reduces bandwidth consumption while maintaining complete AR information through strategic frame selection.
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 reduces resource utilization and improves accuracy by selectively processing data only during low acceleration conditions, enabling efficient and accurate AR information generation and display.
Implementation Method 1
detecting an acceleration condition with respect to the image capture device
Data Source
AI summary
Systems and methods may provide for obtaining or implementing augmented reality information. A logic architecture may be employed to detect a low acceleration condition with respect to an image capture device. The logic architecture may select data from a video associated with the image capture device in response to the low acceleration condition. The logic architecture may also use the data to obtain augmented reality information for the video. Additionally, the logic architecture may modify the video with the augmented reality information, or may display the video with the augmented reality information.