Improvement for Feature Point Extraction Based on Kinect 3D Reconstruction

doi:10.3969/j.issn.1006-2475.2019.11.007

Abstract

Abstract: To solve the problem of low performance-price ratio due to low efficiency and high distortion of feature points extraction in the complex indoor environment of robots, an improved SIFT feature points extraction and matching algorithm is proposed, and on this basis, a SLAM system based on Kinect is built.
The SLAM system front end improves the SIFT feature point extraction method, uses the Gaussian separation fuzzy function, improves the speed of SIFT algorithm to extract the feature point, and uses RANSAC to screen unstable feature points. The SLAM system with improved SIFT feature points extraction method can reconstruct the complex and empty indoor environment with high efficiency and low distortion.

Key words: Kinect 3D reconstruction, indoor 3D reconstruction, SIFT feature point extraction

CLC Number:

TP301.6

CHEN Kai-yang1, LUO Zhi-zao2, WANG Jian-xing2. Improvement for Feature Point Extraction Based on Kinect 3D Reconstruction[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.11.007.

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