3D reconstruction based on KAZE quasi-dense match algorithm

Meng Zhang

doi:10.1117/12.2636426

6 May 2022 3D reconstruction based on KAZE quasi-dense match algorithm

Meng Zhang

Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 121760X (2022) https://doi.org/10.1117/12.2636426
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China

Abstract

The traditional matching algorithm is easy to lose the detail information in the complex background, which is disadvantageous to the 3D reconstruction. To solve these problems, a quasi-dense algorithm based on KAZE feature detection is proposed in this paper, which is helpful to more accurate 3D reconstruction. Firstly, the method uses the KAZE Algorithm to extract the feature points, constructs the feature vector to match, and uses the random sample consistency algorithm to remove the mismatched points. Then the region growth is realized by the polar distance constraint criterion based on the adaptive window diffusion method. The experimental results show that the proposed algorithm can get satisfactory quasi- dense matching results and good disparity map, and can reflect the real scene.

Citation Download Citation

Meng Zhang "3D reconstruction based on KAZE quasi-dense match algorithm", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 121760X (6 May 2022); https://doi.org/10.1117/12.2636426

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