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Published on: December 3, 2013
Recognition of 3D objects based on implicit polynomials
Hilla Ben-Yaacov1, David Malah, Meir Barzohar
1Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel. hilla.ben.yaacov@gmail.com
Researchers developed new 3D rotation invariants from implicit polynomial coefficients. This new method improves 3D object recognition accuracy compared to existing techniques.
Area of Science:
- Computer Vision
- Geometric Algebra
Background:
- Implicit Polynomials (IP) are effective for 3D object representation.
- Existing 3D object recognition methods often rely on pose estimation or specific descriptors like MPEG-7 SSD.
Purpose of the Study:
- To develop novel closed-form expressions for 3D rotation invariants.
- To propose a new 3D object recognition method based on these invariants.
Main Methods:
- Derivation of linear, quadratic, and angular combinations of implicit polynomial coefficients.
- Development of a 3D object recognition algorithm utilizing these new invariants.
Main Results:
- The proposed method demonstrates superior performance in 3D object recognition.
- Outperforms recognition based on implicit polynomial fitting after pose estimation.
- Surpasses the MPEG-7 SSD technique in recognition accuracy.
Conclusions:
- The newly developed 3D rotation invariants offer a robust basis for advanced 3D object recognition.
- This approach provides a significant improvement over current state-of-the-art methods.
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