Synchronizing 3D point cloud from 3D scene flow estimation with 3D Lidar and RGB camera

Hiroki Usami, Hideo Saito, Jun Kawai, Noriko Itani

Research output: Contribution to journalConference articlepeer-review


We present a method for synchronizing three-dimensional (3D) point cloud from 3D scene with estimation using a 3D Lidar and an RGB camera. These 3D points sensed by the 3D Lidar are not captured at the same time, which makes it difficult to measure the correct shape of the object in a dynamic scene. In our method, we generate synchronized 3D points at arbitrary times using linear interpolation in four-dimensional space, time and space. For interpolating the 3D point, we obtain corresponding 3D point matching with the pixel value captured by the RGB camera in a continuous frame. The experimental results demonstrate the effectiveness of the presented method by depicting a synchronized 3D point cloud that is correctly shaped.

Original languageEnglish
Article number426
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Publication statusPublished - 2018
Event3D Image Processing, Measurement (3DIPM), and Applications 2018 - Burlingame, United States
Duration: 2018 Jan 282018 Feb 1

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics


Dive into the research topics of 'Synchronizing 3D point cloud from 3D scene flow estimation with 3D Lidar and RGB camera'. Together they form a unique fingerprint.

Cite this