Automatic Picture Processing via Metadata-Driven Template Selection
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Solution Overview
Problem
Traditional picture processing methods require users to manually select and process multiple images, resulting in high time costs due to the lengthy selection process.
Innovation Solution
A method and apparatus that automatically detect newly-added pictures, acquire information such as photographing time and location, update a picture set, select a matching template, and process the images using the selected template, reducing user time costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional picture processing methods are used where users manually select pictures and templates, then users can have control over the processing workflow, but the time cost for picture processing becomes very high
Solution Approach 1:
The system automatically detects newly added pictures, extracts their metadata (time, location), and selects appropriate processing templates without requiring manual user intervention. The picture set is automatically updated based on the newly added picture's information, enabling the system to serve itself in the picture selection and template matching process.
Solution Approach 2:
The system pre-establishes the relationship between picture metadata and processing templates. When a new picture is added, the system has already prepared the matching logic and template library, allowing for immediate automatic processing without requiring users to manually search or select templates, thus reducing processing time while maintaining quality.
2Productivity
If automatic picture processing is implemented to reduce time costs, then picture processing speed increases, but the complexity of the system increases
Solution Approach 1:
The automatic processing system is divided into distinct functional modules: a detection module that identifies newly added pictures, an information extraction module that retrieves metadata, a picture set update module that manages the to-be-processed picture set, and a template selection module that matches pictures with appropriate templates. This segmentation allows each module to handle a specific task independently, reducing overall system complexity while maintaining high processing efficiency.
3Manufacturing precision
If manual picture selection is required to ensure accurate template matching, then processing accuracy is maintained, but the operation process becomes lengthy and time-consuming
Solution Approach 1:
The system uses the picture's metadata (time and location information) as feedback to automatically determine the most appropriate processing template. By establishing a feedback loop where picture information directly informs template selection, the system achieves accurate matching without requiring manual user judgment, thus maintaining precision while eliminating the time-consuming manual selection process.
Data Source
AI summary
A digital photo processing method, information processing apparatus, and non-transitory computer-readable medium. New digital photos are arranged in chronological order based on capture times of the new digital photos. A determination is made as to whether a subset of the new digital photos are related to each other based on one or a combination of the capture times of the new digital photos and locations at which the new digital photos were captured. One of a plurality of processing templates is selected based on one or a combination of at least one of the capture times of the subset of the new digital photos and at least one of the locations at which the subset of the new digital photos were captured. The subset of the new digital photos is processed according to the selected one of the plurality of processing templates to generate a single image.