Vol.61, No.1, 2019, pp.243-254, doi:10.32604/cmc.2019.05961
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: duzhl@njtech.edu.cn.
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.
SLAM, thread optimization, scene reconstruction, feature point match
Cite This Article
Du, Z., Ma, Y., Li, X., Lu, H. (2019). Fast Scene Reconstruction Based on Improved SLAM. CMC-Computers, Materials & Continua, 61(1), 243–254.