Indoor visual SLAM dataset with various acquisition modalities

Data in Brief

Sergio Rodriguez¹  Imad El Bouazzaoui²  Abdelhafid El Ouardi³  Bastien Vincke³ 

[1] SATIE - CNRS UMR 8029, Paris-Saclay University, France;Corresponding author.;SATIE - CNRS UMR 8029, Paris-Saclay University, France;

关键词: Depth map;    Indoor localization;    RGB-D cameras;    Robotics;   

DOI  :  

来源: DOAJ

【 摘 要 】

The indoor Visual Simultaneous Localization And Mapping (V-SLAM) dataset with various acquisition modalities has been created to evaluate the impact of acquisition modalities on the Visual SLAM algorithm’s accuracy. The dataset contains different sequences acquired with different modalities, including RGB, IR, and depth images in passive stereo and active stereo modes. Each sequence is associated with a reference trajectory constructed with an Structure From Motion (SFM) and Multi View Stereo (MVS) library for comparison. Data were collected using an intrinsically calibrated Intel RealSense D435i camera. The RGB/IR and depth data are spatially aligned, and the stereo images are rectified. The dataset includes various areas, some with low brightness, with changes in brightness, wide, narrow and texture.

【 授权许可】

Unknown