Mobile Camera Image Analysis with Inertial Frame Selection
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Solution Overview
Problem
Existing image analysis techniques on mobile devices consume excessive computational and electrical power, leading to inefficient resource utilization and reduced accuracy due to the analysis of low-quality images.
Innovation Solution
Implement a system that selectively analyzes images based on expected quality determined by environmental sensors, using inertial data to identify high-quality frames for further processing, and employs coarse classifiers to detect object classes before detailed computer vision analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image analysis is performed on all captured images, then object recognition accuracy is improved, but computational power consumption increases excessively
Solution Approach 1:
The system performs preliminary quality assessment of captured images using inertial sensor data before conducting full image analysis. By evaluating image quality metrics (such as motion blur, focus, and composition) in advance, the system identifies and selects only high-quality images for subsequent object recognition processing, thereby avoiding unnecessary computational expenditure on low-quality images while maintaining recognition accuracy.
Solution Approach 2:
The patent replaces traditional image-based quality assessment with inertial sensor data evaluation. Instead of analyzing image content to determine quality, the system uses accelerometer and gyroscope data to predict image quality characteristics, substituting computationally intensive image processing with lighter sensor data processing to achieve the same selection objective.
2Measurement precision
If detailed computer vision analysis is performed on all images, then object detection accuracy is improved, but electrical power consumption increases
Solution Approach 1:
The system performs preliminary filtering of images based on quality metrics derived from inertial sensor data before subjecting images to detailed computer vision analysis. This preliminary action identifies and discards low-quality images that would not contribute meaningfully to object detection accuracy, thereby reducing the electrical power consumption of the stationary image processing components while maintaining detection performance.
3Reliability
If all captured images are processed through image processing apparatus, then analysis completeness is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The system extracts and processes only the essential subset of images that meet quality criteria, separating high-quality images requiring analysis from low-quality images that can be discarded. This extraction approach maintains analysis completeness for relevant images while eliminating waste of computational resources on irrelevant low-quality images, thereby improving overall resource utilization efficiency.
Solution Approach 2:
The system changes the parameter used for image selection from post-capture image quality assessment to pre-processing quality prediction based on inertial sensor parameters. This parameter change enables more efficient resource allocation by identifying suitable images before they enter the resource-intensive processing pipeline, improving productivity without compromising analysis completeness.
Data Source
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AI summary
Methods, systems, and apparatus for efficient image analysis. In some aspects, a system includes a camera configured to capture images, one or more environment sensors configured to detect movement of the camera, a data processing apparatus, and a memory storage apparatus in data communication with the data processing apparatus. The data processing apparatus can access, for each of a multitude of images captured by a mobile device camera, data indicative of movement of the camera at a time at which the camera captured the image. The data processing apparatus can also select, from the images, a particular image for analysis based on the data indicative of the movement of the camera for each image, analyze the particular image to recognize one or more objects depicted in the particular image, and present content related to the one or more recognized objects.