Feature Point Detection for Multi-Object Image Analysis
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Solution Overview
Problem
Existing image analysis techniques are inefficient when dealing with query images containing multiple objects, as they require lengthy comparisons between feature points and object images, and lack methods for handling multiple objects in the query image.
Innovation Solution
An information processing apparatus and method that detects feature points in a query image, determines object images associated with these points, extracts object regions, and cross-checks these regions with corresponding object images to identify objects, using an index table for faster object image determination and detailed comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature points are compared with all object images for each cluster, then object determination accuracy is maintained, but the time required for comparison increases significantly
Solution Approach 1:
The patent divides the comparison process into two stages: first comparing feature points with object images to identify candidate object regions, then performing detailed comparison only within those candidate regions. This segmentation reduces the overall comparison time while maintaining accuracy by focusing computational resources on relevant areas.
Solution Approach 2:
The patent performs preliminary comparison of feature points with object images before the final object determination. This preliminary action identifies candidate object regions that are then subjected to more detailed comparison, avoiding the need to compare all feature points with all object images while maintaining determination accuracy.
2Productivity
If traditional image comparison methods are used for query images containing multiple objects, then comprehensive object detection is attempted, but processing time becomes excessively long
Solution Approach 1:
The patent segments the query image into multiple candidate object regions based on feature point comparison results. Each candidate region is then processed independently through detailed comparison, enabling efficient handling of multiple objects while ensuring comprehensive detection through systematic coverage of all candidate regions.
Solution Approach 2:
The patent performs detailed comparison only on candidate object regions identified through preliminary feature point comparison, rather than examining the entire query image or all possible object images. This partial action approach maintains detection completeness for multiple objects while significantly reducing processing time by focusing computational effort on relevant regions.
Data Source
AI summary
The information processing apparatus (2000) includes a feature point detection unit (2020), a determination unit (2040), an extraction unit (2060), and a comparison unit (2080). A feature point detection unit (2020) detects a plurality of feature points from the query image. The determination unit (2040) determines, for each feature point, one or more object images estimated to include the feature point. The extraction unit (2060) extracts an object region estimated to include the object in the query image in association with the object image of the object estimated to be included in the object region, on the basis of the result of the determination. The comparison unit (2080) cross-checks the object region with the object image associated with the object region and determines an object included in the object region.