https://cvg.cit.tum.de/ 2026-04-22T01:17:08+00:00 FeedCreator 1.8 (info@mypapit.net) 2021-05-14T10:04:59+00:00 2021-05-14T10:04:59+00:00 https://cvg.cit.tum.de/data/datasets/rgbd-dataset/download?rev=1620986699&do=diff Anonymous anonymous@undisclosed.example.com Dataset Download We recommend that you use the 'xyz' series for your first experiments. The motion is relatively small, and only a small volume on an office desk is covered. Once this works, you might want to try the 'desk' dataset, which covers four tables and contains several loop closures.

Dataset Download We recommend that you use the 'xyz' series for your first experiments. The motion is relatively small, and only a small volume on an office desk is covered. Once this works, you might want to try the 'desk' dataset, which covers four tables and contains several loop closures.

2013-01-26T11:07:45+00:00 2013-01-26T11:07:45+00:00 https://cvg.cit.tum.de/data/datasets/rgbd-dataset/file_formats?rev=1359198465&do=diff Anonymous anonymous@undisclosed.example.com File Formats We provide the RGB-D datasets from the Kinect in the following format: Color images and depth maps We provide the time-stamped color and depth images as a gzipped tar file (TGZ). * The color images are stored as 640x480 8-bit RGB images in PNG format.

File Formats We provide the RGB-D datasets from the Kinect in the following format: Color images and depth maps We provide the time-stamped color and depth images as a gzipped tar file (TGZ). * The color images are stored as 640x480 8-bit RGB images in PNG format.

2011-08-04T15:13:34+00:00 2011-08-04T15:13:34+00:00 https://cvg.cit.tum.de/data/datasets/rgbd-dataset/intrinsic_calibration?rev=1312470814&do=diff Anonymous anonymous@undisclosed.example.com Intrinsic Camera Calibration of the Kinect The Kinect has a factory calibration stored onboard, based on a high level polynomial warping function. The OpenNI driver uses this calibration for undistorting the images, and for registering the depth images (taken by the IR camera) to the RGB images. Therefore, the depth images in our datasets are reprojected into the frame of the color camera, which means that there is a 1:1 correspondence between pixels in the depth map and the color image.

Intrinsic Camera Calibration of the Kinect The Kinect has a factory calibration stored onboard, based on a high level polynomial warping function. The OpenNI driver uses this calibration for undistorting the images, and for registering the depth images (taken by the IR camera) to the RGB images. Therefore, the depth images in our datasets are reprojected into the frame of the color camera, which means that there is a 1:1 correspondence between pixels in the depth map and the color image.

2021-05-14T07:21:56+00:00 2021-05-14T07:21:56+00:00 https://cvg.cit.tum.de/data/datasets/rgbd-dataset/online_evaluation?rev=1620976916&do=diff Anonymous anonymous@undisclosed.example.com Submission form for automatic evaluation of RGB-D SLAM results

Submission form for automatic evaluation of RGB-D SLAM results

2012-06-18T14:01:07+00:00 2012-06-18T14:01:07+00:00 https://cvg.cit.tum.de/data/datasets/rgbd-dataset/rgbdslam_eval?rev=1340028067&do=diff Anonymous anonymous@undisclosed.example.com How to evaluate RGBD-SLAM with our datasets? This page describes how to evaluate [RGBD-SLAM] using our [Kinect datasets]. Code download and compilation cd ~/ros svn checkout https://svncvpr.in.tum.de/cvpr-ros-pkg/trunk cvpr-ros-pkg rosmake rgbdslam_eval --rosdep-install

How to evaluate RGBD-SLAM with our datasets? This page describes how to evaluate [RGBD-SLAM] using our [Kinect datasets]. Code download and compilation cd ~/ros svn checkout https://svncvpr.in.tum.de/cvpr-ros-pkg/trunk cvpr-ros-pkg rosmake rgbdslam_eval --rosdep-install

2021-05-14T10:50:15+00:00 2021-05-14T10:50:15+00:00 https://cvg.cit.tum.de/data/datasets/rgbd-dataset/tools?rev=1620989415&do=diff Anonymous anonymous@undisclosed.example.com Useful tools for the RGB-D benchmark We provide a set of tools that can be used to pre-process the datasets and to evaluate the SLAM/tracking results. The scripts can be [downloaded here]. To checkout the repository using subversion, run svn checkout https://svncvpr.in.tum.de/cvpr-ros-pkg/trunk/rgbd_benchmark/rgbd_benchmark_tools

Useful tools for the RGB-D benchmark We provide a set of tools that can be used to pre-process the datasets and to evaluate the SLAM/tracking results. The scripts can be [downloaded here]. To checkout the repository using subversion, run svn checkout https://svncvpr.in.tum.de/cvpr-ros-pkg/trunk/rgbd_benchmark/rgbd_benchmark_tools