Motion Filter Module for Panoramic Photography
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Solution Overview
Problem
Handheld personal electronic devices face challenges in capturing and processing panoramic images due to difficulties in determining exposure settings, blurring, parallax issues, and post-processing problems such as image alignment and distortion, which are not efficiently addressed by existing technologies.
Innovation Solution
The use of positional sensors like MEMS accelerometers and gyrometers to perform motion filtering, image registration, geometric corrections, and stitching of images, allowing for the creation of visually appealing panoramic images by selecting relevant image data and avoiding redundant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all captured image frames are processed to create panoramic image, then complete coverage of panoramic scene is achieved, but computational intensity and memory footprint increase significantly
Solution Approach 1:
The motion filter module extracts and discards redundant image frames from the captured sequence based on motion analysis. Only non-redundant frames are passed to the panoramic assembly module, reducing computational load while maintaining complete scene coverage. This selective extraction resolves the contradiction by removing unnecessary processing of duplicate frames.
Solution Approach 2:
The system changes the parameter of frame selection from processing all frames to processing only non-redundant frames identified through motion analysis. This parameter change in the processing pipeline reduces computational intensity and memory footprint while preserving the完整性 of the panoramic scene coverage.
2Manufacturing precision
If image frames are captured at high rate to ensure complete scene coverage, then all scene elements are captured, but motion blurring increases due to device movement
Solution Approach 1:
The motion filter module uses motion detection to identify and remove frames that exhibit excessive motion blur caused by high capture rates. The harmful effect of motion blur during rapid capture is converted into a useful filtering criterion, allowing the system to discard blurred frames while retaining sharp ones, thus maintaining scene coverage completeness without sacrificing image sharpness.
3Power
If positional sensors are used to filter image frames, then computational load is reduced, but device complexity increases
Solution Approach 1:
The device uses its own built-in positional sensors (accelerometer, gyroscope) to perform self-diagnosis and self-filtering of image frames. The sensors already present in the device provide motion data that the processing module uses to identify redundant frames, eliminating the need for external filtering equipment. This self-service approach reduces computational load without significantly increasing device complexity.
4Manufacturing precision
If redundant image frames are processed, then complete panoramic coverage is ensured, but memory footprint increases
Solution Approach 1:
The motion filter module extracts and removes redundant image frames from the capture sequence before they are passed to the panoramic assembly module. By extracting only the essential non-redundant frames needed for complete scene coverage, the system significantly reduces memory footprint while ensuring that all unique scene elements are included in the final panoramic image.
Data Source
AI summary
This disclosure pertains to devices, methods, and computer readable media for perforating positional sensor-assisted panoramic photography techniques in handheld personal electronic devices. Generalized steps that may be used to carry out the panoramic photography techniques described herein include, but are not necessarily limited to: 1.) acquiring image data from the electronic device's image sensor; 2.) performing “motion filtering” on the acquired image data, e.g., using information returned from positional sensors of the electronic device to inform the processing of the image data; 3.) performing image registration between adjacent captured images; 4.) performing geometric corrections on captured image data, e.g., due to perspective changes and/or camera rotation about a non-center of perspective (COP) camera point; and 5.) “stitching” the captured images together to create the panoramic scene, e.g., blending the image data in the overlap area between adjacent captured images. The resultant stitched panoramic image may be cropped before final storage.