A Method of Generating Measurable Panoramic Image for Indoor Mobile Measurement System
Abstract
This paper designs a technique route to generate high-quality panoramic image with depth information, which involves two critical research hotspots: fusion of LiDAR and image data and image stitching. For the fusion of 3D points and image data, since a sparse depth map can be firstly generated by projecting LiDAR point onto the RGB image plane based on our reliable calibrated and synchronized sensors, we adopt a parameter self-adaptive framework to produce 2D dense depth map. For image stitching, optimal seamline for the overlapping area is searched using a graph-cuts-based method to alleviate the geometric influence and image blending based on the pyramid multi-band is utilized to eliminate the photometric effects near the stitching line. Since each pixel is associated with a depth value, we design this depth value as a radius in the spherical projection which can further project the panoramic image to the world coordinate and consequently produces a high-quality measurable panoramic image. The purposed method is tested on the data from our data collection platform and presents a satisfactory application prospects.
Keywords
Cite
@article{arxiv.2010.14270,
title = {A Method of Generating Measurable Panoramic Image for Indoor Mobile Measurement System},
author = {Hao Ma and Jingbin Liu and Zhirong Hu and Hongyu Qiu and Dong Xu and Zemin Wang and Xiaodong Gong and Sheng Yang},
journal= {arXiv preprint arXiv:2010.14270},
year = {2020}
}