Panoramic Image Correction Using Face-Selected Sub-Images
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Solution Overview
Problem
Existing image processing technologies face challenges in efficiently synthesizing panoramic images from multiple sub-images while maintaining uniform brightness and chroma, especially when attractive features like faces are present, leading to increased processing time and suboptimal image correction.
Innovation Solution
An image processing apparatus that includes a face recognizing unit, a sampling image selecting unit, a sampling unit, a correction parameter establishing unit, and an image processing unit, which identifies and selects sub-images with prominent features, extracts features from sampled pixels, and establishes a correction parameter for uniform image correction across multiple sub-images, prioritizing features like faces, center positioning, and orientation for improved attractiveness and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixels are sampled from the entire panoramic image after synthesizing all sub-images, then the correction parameter can be established based on the complete panoramic view, but the synthesization time increases significantly due to the large image size
Solution Approach 1:
The patent divides the panoramic image into multiple sub-images and selects specific sub-images (those containing faces) for sampling. Instead of processing the entire large panoramic image, the system segments the problem by working with smaller sub-image portions that contain the most important features for correction parameter establishment.
Solution Approach 2:
The patent performs preliminary selection of sub-images containing faces before establishing correction parameters. By pre-identifying which sub-images contain faces using face recognition technology, the system prepares the optimal sampling sources in advance, avoiding the need to process the entire panoramic image.
2Productivity
If one sub-image is selected for sampling to reduce processing time, then the synthesization speed improves, but the correction may not be suitable for the main portion of the panoramic image if the selected sub-image does not contain attractive features
Solution Approach 1:
The patent introduces face recognition technology as an intermediary to identify which sub-images contain faces. This intermediary step ensures that the selected sub-image for sampling actually contains the attractive features (faces) that users care about, bridging the gap between speed and quality.
Solution Approach 2:
The patent changes the selection criterion from arbitrary or uniform sampling to intelligent sampling based on the presence of faces. By detecting faces in sub-images, the system identifies regions with attractive features and prioritizes those for sampling, ensuring correction quality matches user expectations.
3Stability of the object's composition
If correction parameters are established by averaging values from multiple sub-images, then uniformity across images is improved, but the attractive main portion with faces may be lost in the averaging process
Solution Approach 1:
The patent applies local quality by treating sub-images containing faces differently from those without. Instead of uniform averaging across all sub-images, the system prioritizes sampling from sub-images with faces, ensuring that the attractive main portion retains its characteristics while still achieving overall uniformity through the correction process.
Data Source
AI summary
An image processing apparatus synthesizing a plurality of sub-images in a panoramic way to create a panoramic image includes a face recognizing unit recognizing a person's face from a plurality of the sub-images, a sampling image selecting unit selecting a sub-image which has a face recognized by the face recognizing unit, out of a plurality of the sub-images as a sampling image, a sampling unit sampling a plurality of pixels from the selected sampling image.