Time-lapse Image Normalization for Personal Appearance Tracking
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Solution Overview
Problem
Consumers face difficulties in capturing consistently posed and lighted images at home to track progress in personal care routines due to lack of technical skill and professional photography equipment, and images from uncontrolled environments are challenging to process reliably.
Innovation Solution
A method for creating time-lapse video using a computer system that captures and normalizes images from various angles and lighting conditions, allowing users to generate time-series images without professional equipment, which are then synthesized into representative images to demonstrate changes over time, such as skin improvements, using mobile computing devices and cloud processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If consistently posed and lighted images are captured to track personal appearance changes, then measurement precision is improved, but device complexity and ease of operation worsen due to requiring professional photography equipment and technical skill
Solution Approach 1:
The patent uses mobile device cameras to capture images that copy the subject's appearance, then processes these copies through normalization algorithms to create standardized representations. This eliminates the need for professional photography equipment while maintaining measurement capability through digital processing of the captured image copies
Solution Approach 2:
The system changes the parameters of captured images through normalization processes, adjusting lighting, pose, and other variables to standardize the images. This allows consumer-grade cameras to produce images suitable for precise measurement by transforming the raw captured parameters into standardized measurement parameters
2Measurement precision
If consistently posed and lighted images are captured to track personal appearance changes, then measurement precision is improved, but ease of operation worsens due to requiring technical skill and controlled conditions
Solution Approach 1:
The system performs self-service by automatically normalizing images captured under varying conditions. The normalization algorithm automatically adjusts for lighting changes, pose variations, and other environmental factors without requiring the user to manually control these parameters, making the process easy for consumers to operate while maintaining measurement precision
Solution Approach 2:
The normalization process acts as an intermediary between the raw captured images and the final measurement analysis. It mediates the differences in lighting, pose, and environmental conditions by transforming the varied captured images into standardized representations suitable for precise comparison
3Ease of operation
If images are captured in uncontrolled environments without professional equipment, then ease of operation is improved, but measurement precision and reliability worsen due to variations in lighting and camera conditions
Solution Approach 1:
The system converts the harmful effect of varying lighting and environmental conditions into a benefit by using these variations as input data that the normalization algorithm can process. Instead of requiring controlled conditions, the system accepts uncontrolled environment images and uses digital processing to extract reliable measurement information, turning the disadvantage of environmental variability into an opportunity for robust automated processing
Data Source
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AI summary
A computer system creates time lapse video of a live subject to help assess effects of skin treatments, use of cosmetics, or personal care routines over time. In one aspect, the computer system obtains a set of digital source images (e.g., from video or a series of still images) of a region of interest of a live subject (e.g., the face of the live subject or a portion thereof) captured in a first time period; normalizes the set of digital source images; obtains a first representative image that includes the region of interest by synthesizing or selecting it from the set of digital source images; and combines the first representative image with additional representative images from other time periods to form a time lapse video of the region of interest of the live subject.