Image Feature Extraction for Object Re-Identification
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Solution Overview
Problem
Current monitoring camera systems face challenges in accurately re-identifying objects across different cameras due to issues like camera orientation, manual calibration requirements, and redundant processing steps, which decrease efficiency and increase computational burden.
Innovation Solution
An image processing apparatus that includes an image feature extraction unit, a region extraction unit, a correction unit, an identification feature extraction unit, and an identification unit, which work together to extract and correct image features, normalize object orientation, and identify objects based on re-identification features, eliminating the need for manual calibration and reducing redundant processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual camera calibration is performed to acquire orientation information, then accuracy of object re-identification is improved, but labor cost and device complexity increase
Solution Approach 1:
The system automatically acquires camera orientation information by detecting the inclination of objects in images without requiring manual calibration. The correction information is derived self-service from the image data itself, eliminating the need for labor-intensive manual calibration processes while maintaining re-identification accuracy.
Solution Approach 2:
The system performs preliminary acquisition of correction information from image features before the actual re-identification process. By pre-processing the images to extract orientation data and generate correction information in advance, the system eliminates the need for manual calibration at the time of use, reducing labor cost while preserving measurement precision.
2Reliability
If separate processing is performed for correcting object inclination and extracting object region, then completeness of processing is improved, but calculation amount and productivity decrease
Solution Approach 1:
The system merges the correction information acquisition process with the object region extraction process by using the same image feature extraction unit for both purposes. The correction information and object region are obtained simultaneously from the extracted image features, eliminating redundant calculations while ensuring both correction and extraction are performed on the same object region for complete and reliable processing.
3Reliability
If separate processing is performed for correcting object inclination and extracting object region, then completeness of processing is improved, but device complexity increases
Solution Approach 1:
The image feature extraction unit serves multiple functions: it extracts features for both obtaining correction information and extracting object regions. This multi-functional approach consolidates the processing procedures into a single unified process, reducing device complexity while maintaining the completeness of both correction and extraction operations.
Solution Approach 2:
The system combines the correction information acquisition and object region extraction into a single integrated processing flow. By using the same extracted image features for both purposes and performing them in sequence without redundant steps, the system reduces the number of processing procedures while ensuring both operations are completed, thereby reducing device complexity without sacrificing reliability.
Data Source
AI summary
An image processing apparatus includes an image feature extraction unit configured to extract an image feature from an input image, a region extraction unit configured to extract a foreground region from the input image based on the image feature, an acquisition unit configured to acquire correction information based on the image feature, a correction unit configured to correct the foreground region using the correction information, an identification feature extraction unit configured to extract a feature for identification from the foreground region corrected by the correction unit, and an identification unit configured to identify an object in the input image based on the feature for the identification.