@article{Chen2025, 
author = {Xiao-Rui Chen and Meng-Fei Yang and Gao Zhang and Wu Zhang and Jing Peng and Zheng Gu and Xiang-Jin Deng and Liu-Zhi Yang and Fei Yang and Yun Yang and Shou-Qian Sun and Ruo-Feng Tong and Min Tang},
title = {3D Point Cloud Matching Based Selfie Generation for Chang’e-5},
year = {2025},
journal = {Journal of Computer Science and Technology},
volume = {40},
number = {1},
pages = {85-98},
keywords = {GPU computing, image stitching, Chang’e-5, 3D point cloud matching, selfie generation},
url = {https://www.sciopen.com/article/10.1007/s11390-024-3667-6},
doi = {10.1007/s11390-024-3667-6},
abstract = {Generating selfie images on the surface of a celestial body poses several challenges, including the position of the robotic arm, camera field of view, and limited shooting time. To address these challenges, the PCMIS (3D Point Cloud Matching Based Image Stitching) algorithm is designed, along with a corresponding shooting plan. This algorithm establishes a correspondence between depth and color information, enabling the generation of stitching views under any given view parameter. Furthermore, the algorithm is accelerated using GPU processing, resulting in a significant reduction in stitching time. The algorithm is successfully applied to generate selfie images for the Chang’e-5 mission.}
}