Portrait Person Identification System with Dynamic Analysis
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Solution Overview
Problem
Existing person identification systems are ineffective in identifying individuals depicted in portraits, as they are designed primarily for analyzing actual person images and struggle with portrait images.
Innovation Solution
A system that receives portrait data, extracts feature points through image analysis, checks these points against stored individual data, and identifies the person with a corresponding probability level, displaying the results along with reasons and property information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a person identification system designed for actual person images is used, then it can effectively identify real people, but it fails to identify individuals depicted in portraits
Solution Approach 1:
The system dynamically adjusts the analysis procedure based on the input image type. When a portrait is detected, the system switches to a portrait-specific analysis mode that extracts features suitable for artistic representations, whereas actual person images are processed using standard biometric analysis methods. This dynamic adaptation allows the single system to effectively handle both portrait and real person identification tasks.
Solution Approach 2:
The system changes the analysis parameters and feature extraction methods according to the image type. For portraits, it employs parameters optimized for artistic styles, brush strokes, and painted features, while for actual persons, it uses parameters suited for photographic details and natural facial structures. This parameter transformation enables reliable identification across both image categories.
2Adaptability or versatility
If the analysis procedure is made more complex to handle portrait images, then portrait identification capability improves, but processing time and computational resources increase
Solution Approach 1:
The system segments the analysis process into distinct modules: one for detecting image type (portrait vs. actual person), another for extracting appropriate features based on the detected type, and a final module for comparison and identification. This segmentation allows the system to apply complex portrait analysis only when necessary, rather than processing all images through the full complex procedure, thus reducing overall processing time while maintaining portrait identification capability.
Solution Approach 2:
The system performs preliminary classification of the input image to determine whether it is a portrait or an actual person image before initiating the main identification process. This preliminary action enables the system to select the appropriate analysis procedure in advance, avoiding unnecessary computational steps and reducing processing time for both portrait and non-portrait images.
Data Source
AI summary
The present invention is to provide a system, a method, and a program for identifying a person depicted in a portrait. The system for identifying a person depicted in a portrait 1 receives input of portrait data of the portrait, stores different individual data depending on a plurality of persons, extracts a feature point of the received portrait by image analysis, checks the extracted feature point against the individual data, identifies a person depicted in the portrait from the check result, and displays the identification result together with a probability corresponding to an identical level.