2D Image Recognition Using 3D Class Models
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Solution Overview
Problem
Current class recognition systems face challenges in recognizing instances of classes from various viewpoints and distances due to variability in object shape and visual appearance, and they often require 3D range information which is difficult to obtain in uncontrolled environments.
Innovation Solution
A system and method for recognizing classes in 2D images using 3D class models that incorporate both range and intensity information, allowing for alignment and comparison of image features with 3D class models using pose-invariant appearance descriptors and geometric transformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D range information is used to improve recognition accuracy, then recognition precision is improved, but device complexity and data acquisition difficulty increase
Solution Approach 1:
The patent extracts and utilizes only the intensity information from the 3D range and intensity data, discarding the range component. This allows the system to achieve accurate class recognition using only 2D intensity images while avoiding the complexity of processing and acquiring 3D range data.
Solution Approach 2:
The patent creates a 3D class model database that stores both range and intensity information during the training phase, but during recognition it only requires intensity images. The stored 3D models serve as references that can be matched against 2D intensity images, effectively copying the essential features needed for recognition without requiring full 3D data at recognition time.
2Reliability
If 3D class models with both range and intensity are used, then recognition reliability is improved, but ease of operation deteriorates due to difficulty in obtaining 3D range data
Solution Approach 1:
The patent extracts and utilizes only the intensity information from the 3D range and intensity data, discarding the range component. This allows the system to achieve accurate class recognition using only 2D intensity images while avoiding the complexity of processing and acquiring 3D range data.
3Adaptability or versatility
If pose-invariant appearance descriptors are used, then adaptability to different viewpoints is improved, but computational complexity increases
Solution Approach 1:
The patent pre-computes pose-invariant appearance descriptors and stores them in the 3D class model database during the training phase. This preliminary computation allows the system to quickly compare pre-processed descriptors during recognition without performing complex calculations in real-time, thus achieving viewpoint invariance without excessive computational burden during operation.
Data Source
AI summary
A system and method for recognizing instances of classes in a 2D image using 3D class models and for recognizing instances of objects in a 2D image using 3D class models. The invention provides a system and method for constructing a database of 3D class models comprising a collection of class parts, where each class part includes part appearance and part geometry. The invention also provides a system and method for matching portions of a 2D image to a 3D class model. The method comprises identifying image features in the 2D image; computing an aligning transformation between the class model and the image; and comparing, under the aligning transformation, class parts of the class model with the image features. The comparison uses both the part appearance and the part geometry.