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Fast Scene Reconstruction Based on Improved SLAM

Zhenlong Du1,*, Yun Ma1, Xiaoli Li1, Huimin Lu2

School of Computer Science and Technology, Nanjing TECH University, Nanjing, 211816, China.
School of Engineering, Kyushu Institute of Technology, Kyushu 804-8550, Japan.

* Corresponding Author: Zhenlong Du. Email: email.

Computers, Materials & Continua 2019, 61(1), 243-254.


Simultaneous location and mapping (SLAM) plays the crucial role in VR/AR application, autonomous robotics navigation, UAV remote control, etc. The traditional SLAM is not good at handle the data acquired by camera with fast movement or severe jittering, and the efficiency need to be improved. The paper proposes an improved SLAM algorithm, which mainly improves the real-time performance of classical SLAM algorithm, applies KDtree for efficient organizing feature points, and accelerates the feature points correspondence building. Moreover, the background map reconstruction thread is optimized, the SLAM parallel computation ability is increased. The color images experiments demonstrate that the improved SLAM algorithm holds better real-time performance than the classical SLAM.


Cite This Article

APA Style
Du, Z., Ma, Y., Li, X., Lu, H. (2019). Fast scene reconstruction based on improved SLAM. Computers, Materials & Continua, 61(1), 243-254.
Vancouver Style
Du Z, Ma Y, Li X, Lu H. Fast scene reconstruction based on improved SLAM. Comput Mater Contin. 2019;61(1):243-254
IEEE Style
Z. Du, Y. Ma, X. Li, and H. Lu "Fast Scene Reconstruction Based on Improved SLAM," Comput. Mater. Contin., vol. 61, no. 1, pp. 243-254. 2019.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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