This study integrates RGB-D sensor and DSLR camera to generate point cloud models of indoor environment. There are four main steps in the proposed procedure: (1) Structure from Motion (SfM) method is used to reconstruct the camera position and parameters from multiple color images. High resolution images captured by DSLR cameras can provide more accurate ray intersection condition. (2) Using the software based on Clustering Views for Multi-view Stereo (CMVS) method to construct a dense matching point clouds. (3) According to feature points extracted in SfM reconstruction, using Random Sample Consensus (RANSAC) method to select the feature points. Then, transfer the RGB-D point clouds to the same coordinate system as the dense matching point clouds via 3D Similarity transformation. (4) Generate a complete model from integrated point clouds. Experimental results demonstrate that the proposed data processing procedure can efficiently generate 3D point cloud models of indoor environments.
|出版狀態||已出版 - 2015|
|事件||36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015 - Quezon City, Metro Manila, Philippines|
持續時間: 24 10月 2015 → 28 10月 2015
|???event.eventtypes.event.conference???||36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015|
|城市||Quezon City, Metro Manila|
|期間||24/10/15 → 28/10/15|