Jinxing Niu^1,*, Qingsheng Hu¹, Yi Niu¹, Tao Zhang¹, Sunil Kumar Jha²

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3713-3724, 2021, DOI:10.32604/cmc.2021.017418

Abstract Real-time dense reconstruction of indoor scenes is of great research value for the application and development of service robots, augmented reality, cultural relics conservation and other fields. ORB-SLAM2 method is one of the excellent open source algorithms in visual SLAM system, which is often used in indoor scene reconstruction. However, it is time-consuming and can only build sparse scene map by using ORB features to solve camera pose. In view of the shortcomings of ORB-SLAM2 method, this article proposes an improved ORB-SLAM2 solution, which uses a direct method based on light intensity to solve the camera pose. It can greatly… More >

Zhenlong Du^1,*, Yun Ma¹, Xiaoli Li¹, Huimin Lu²

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 243-254, 2019, DOI:10.32604/cmc.2019.05961

Abstract 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… More >