Two different capsules and conventional endoscope cameras, with high and low resolution were used, so as to generate variety in camera specifications and lighting conditions.To the best of authors' knowledge, this is the very first dataset published to be used in capsule endoscopy SLAM tasks, with timed 6 DoF pose data and high precision 3D map ground truth.
Specifically, 18, 5 and 12 sub-datasets exist for colon, small intestine and stomach respectively. The dataset is divided into 35 sub-datasets. The ex-vivo part of the dataset includes standard as well as capsule endoscopy recordings. We introduce an endoscopic SLAM dataset which consists of both ex-vivo and synthetically generated data. EndoSLAM Dataset and an Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos
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