Wearable Camera Motion Blur Avoidance via Image Clustering
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Solution Overview
Problem
Wearable and mountable cameras often capture blurry photos due to camera movement, especially when used by photographers on the go, as they lack effective mechanisms to mitigate motion blur and adjust exposure time accordingly.
Innovation Solution
A camera system that captures a cluster of photographs and uses image processing techniques to select the least blurry image, incorporating a gyroscope or accelerometer to determine motion and adjust shutter time based on both motion and environmental brightness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the camera captures a single photograph in dynamic conditions, then the operation is simple and fast, but the photo quality deteriorates due to motion blur
Solution Approach 1:
The camera captures multiple photographs (a cluster of photos) instead of a single photo, dividing the capture process into multiple discrete shots. This segmentation allows the system to select the best quality image from the cluster, thereby improving photo quality while maintaining operational efficiency through automated selection.
Solution Approach 2:
The system uses blur detection algorithms to analyze captured images and provide feedback on image quality. Based on this feedback, the camera automatically selects the least blurry photograph from the captured cluster, creating a closed-loop system that continuously optimizes photo quality without requiring manual intervention.
2Illumination intensity
If the camera uses a longer exposure time to improve image quality in low light, then the photo brightness improves, but motion blur increases due to camera movement
Solution Approach 1:
The camera dynamically adjusts exposure time based on real-time detection of camera motion and environmental lighting conditions. When motion is detected, the system shortens exposure time to prevent blur; when motion is minimal and lighting is sufficient, it extends exposure time to improve brightness and quality, creating an adaptive exposure system.
Solution Approach 2:
The system changes the exposure time parameter dynamically based on detected conditions. By monitoring camera motion and brightness levels, the camera adjusts the exposure time parameter in real-time, optimizing the balance between capturing sufficient light and preventing motion-induced blur.
3Manufacturing precision
If the camera captures a cluster of photographs to reduce blur, then the photo quality improves, but the time and storage requirements increase
Solution Approach 1:
The camera captures a limited cluster of photographs (excessive action) but processes and selects only the single best quality image (partial action). This approach ensures sufficient photo quality by capturing multiple frames while minimizing time loss through automated selection that requires processing only the essential subset of images.
Data Source
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AI summary
Various embodiments provide a wearable camera that is configured to take a cluster of photographs and use image processing techniques to select a photograph with a lesser amount of blur than other photographs in the cluster. The wearable camera can include one or more of a gyroscope or accelerometer for ascertaining the camera's motion. Motion data associated with the camera's motion is utilized to ascertain when to take an automatic photograph.