Object Dataset Capture With Quality-Based Image Buffering
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Solution Overview
Problem
Existing 3D data capture methods lack guidance for users to correctly position user devices, leading to inefficient and inaccurate data collection.
Innovation Solution
A computer-implemented method that analyzes a stream of images to determine capture characteristics, buffers relevant portions for further processing, and provides real-time feedback to users for optimal data capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all captured images are buffered for further processing, then complete data is obtained, but storage resources are wasted on low-quality images
Solution Approach 1:
The system performs preliminary quality assessment of captured images by analyzing capture characteristics (lighting conditions, device position, focus status) before buffering the images for further processing. This preliminary evaluation prevents low-quality images from consuming storage resources while ensuring high-quality images are retained for 3D reconstruction.
Solution Approach 2:
The imaging system automatically evaluates its own capture quality using sensors and metadata (exposure settings, focus distance, device orientation) without requiring external inspection. The system self-determines which images meet quality thresholds and should be buffered, enabling autonomous quality-based filtering.
2Measurement precision
If continuous analysis of image stream is performed, then capture quality is optimized, but processing time increases
Solution Approach 1:
The system performs partial analysis by evaluating only critical capture characteristics (lighting adequacy, device stability, focus status) rather than comprehensively analyzing all image parameters. This selective approach maintains quality assessment accuracy while significantly reducing processing overhead and time consumption.
Solution Approach 2:
The continuous analysis is implemented as periodic sampling of capture characteristics at defined intervals during the imaging process, rather than continuous frame-by-frame analysis. This periodic evaluation maintains quality optimization while reducing computational burden and processing time.
3Quantity of substance
If buffering is performed without quality assessment, then all data is preserved, but data quality for further processing deteriorates
Solution Approach 1:
The system changes the parameter of data preservation from quantity-based (buffering all images) to quality-based (buffering only images meeting specific capture characteristic thresholds). By setting and evaluating parameters such as minimum lighting levels, acceptable device stability ranges, and focus quality metrics, the system ensures high manufacturing precision of captured data while maintaining efficient storage utilization.
Data Source
AI summary
Systems and methods for generating a dataset associated with an object-of-interest. The method includes acquiring, by an imaging system, a stream of images of the object-of-interest and analyzing the stream of images by determining whether one or more capture constraint is met. The analysis is performed by continuously executing the following steps. If one or more capture characteristics is met for a portion of the stream of images, the portion of the stream of images is buffered thereby defining the dataset, the dataset being fitted for further processing. If the one or more capture characteristic is not met for the portion of the stream of images, the buffering is precluded until determination is made that the capture characteristic of a subsequent portion of the stream of images is met. The analyzing of the stream of images is stopped in response to a stopping condition is met.