Adaptive Face Area Extraction for Image Composition
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Solution Overview
Problem
Existing image processing techniques fail to generate appropriately composited image data by not accurately specifying partial images based on the number and size of face areas in target images, leading to suboptimal composition results.
Innovation Solution
An image processing apparatus that acquires target and template image data, detects face areas, and generates composited image data by specifying partial images of appropriate size and shape based on the number of face areas, ensuring accurate composition within specific areas of the template image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed-size partial image is extracted from the target image, then the composition process is simple, but the composited image does not adapt well when multiple face areas are present
Solution Approach 1:
The patent applies dynamics by making the partial image extraction parameters adaptive rather than fixed. The extraction frame size and position are dynamically adjusted based on the detected face areas. When multiple face areas are detected, the system calculates an extraction frame that encompasses all faces, automatically adapting the extraction logic to different scene compositions without requiring manual intervention or complex rule-based systems.
Solution Approach 2:
The patent changes parameters based on detection results. The extraction frame's position coordinates (x1, y1, x2, y2) and dimensions are modified according to the number and positions of detected face areas. This parameter adaptation allows the same extraction logic to handle both single-face and multi-face scenarios effectively, resolving the contradiction between adaptability and complexity.
2Manufacturing precision
If a large partial image is extracted to include all face areas, then all faces are captured, but the composition quality decreases due to excessive background inclusion
Solution Approach 1:
The patent applies local quality by making different regions of the extracted partial image serve different purposes. The extraction frame is precisely positioned to include all face areas while minimizing unnecessary background. The composition process then focuses on properly positioning and scaling the extracted region within the template, ensuring that face areas are prominently displayed while background elements are appropriately limited. This local optimization achieves high composition precision without requiring the entire extracted image to be of uniform high quality.
Solution Approach 2:
The patent performs preliminary extraction and positioning of the partial image before final composition. By pre-calculating the extraction frame that optimally includes all face areas and then positioning this extracted region within the template image, the system achieves precise face composition. This two-stage approach (extraction followed by positioning) allows the system to separate the concerns of capturing all faces from the concerns of achieving optimal composition quality.
3Ease of operation
If the extracted image is always centered in the template, then the composition process is simple, but the face areas may not be optimally positioned in the template's specific area
Solution Approach 1:
The patent uses feedback from the detected face area positions to determine the optimal placement of the extracted partial image within the template. Rather than always centering the extraction, the system calculates the position based on the distribution of face areas and the dimensions of the template's specific composition area. This feedback mechanism ensures that extracted images are positioned to optimally display faces within the template constraints, achieving high positioning accuracy while maintaining automated operation.
Solution Approach 2:
The patent performs preliminary calculation of the extraction frame position and size before composition based on face detection results. This pre-positioning step determines the optimal extraction parameters that will result in proper face placement within the template. By calculating the extraction frame to match the template's specific area dimensions and considering face area distributions, the system achieves accurate face positioning automatically, combining ease of operation with high precision.
Data Source
AI summary
An image processing apparatus including: a processor; and a memory storing instructions that, when executed by the processor, cause the apparatus to perform: acquiring target image data and template image data; specifying a partial image in a target image based on a result of detecting a face area; and compositing the specified partial image in a specific area in a template image, wherein, when a single face area is detected, a first partial image including the single face area and having a size determined based on a size of the single face area is specified, and, when a plurality of face areas are detected, a second partial image including at least one of the face areas, having a shape homothetic to the specific area and having a maximum size within the target image is specified.