PUTKK – PUT Kinect 1 & Kinect 2 data set

Although the introduction of commercial RGB-D sensors has enabled significant progress in the visual navigation methods for mobile robots, the structured-light-based sensors, like Microsoft Kinect and Asus Xtion Pro Live have some important limitations with respect to their range, field of view, and depth measurements accuracy. The recent introduction of the second generation Kinect, which is based on the time-of-flight measurement principle, brought to the robotics and computer vision researchers a sensor that overcomes some of these limitations. However, as the new Kinect is, just like the older one, intended for computer games and human motion capture rather than for navigation, it is unclear how much the navigation methods, such as visual odometry and SLAM can benefit from the improved parameters. While there are many publicly available RGB-D data sets, only few of them provide ground truth information necessary for evaluating navigation methods, and to the best of our knowledge, none of them contains sequences registered with the new version of Kinect. Therefore, this paper describes a new RGB-D data set, which is a first attempt to systematically evaluate the indoor navigation algorithms on data from two different sensors in the same environment and along the same trajectories. This data set contains synchronized RGB-D frames from both sensors and the appropriate ground truth from an external motion capture system based on distributed cameras. We describe in details the data registration procedure, and then evaluate our RGB-D visual odometry algorithm on the obtained sequences, investigating how the specific properties and limitations of both sensors influence the performance of this navigation method.

Before using PUTKK, please read PUTKK usage guideline

RGB-D images of PUTKK SLAM sequences with ground truth files:

• PUTKK Sequence 1 Kin v1
• PUTKK Sequence 1 Kin v2
• PUTKK Sequence 2 Kin v1
• PUTKK Sequence 2 Kin v2
• PUTKK Sequence 3 Kin v1
• PUTKK Sequence 3 Kin v2
• PUTKK Sequence 4 Kin v1
• PUTKK Sequence 4 Kin v2

RGB-D images of PUTKK different speed sequences with ground truth files:

• PUTKK Sequence 5 Kin v1
• PUTKK Sequence 5 Kin v2
• PUTKK Sequence 6 Kin v1
• PUTKK Sequence 6 Kin v2
• PUTKK Sequence 7 Kin v1
• PUTKK Sequence 7 Kin v2
• PUTKK Sequence 8 Kin v1
• PUTKK Sequence 8 Kin v2

Camera parameters:

• Kinect1.xml
• Kinect2.xml

Exemplary RGB videos created based on recorded RGB images from Kinect v1 & Kinect v2:

Scene reconstruction of PUTKK using ground truth with FastFusion:

RGB camera video in PUTKK SLAM sequences in youtube:

• PUTKK – Sequence 1 Kinect v1
• PUTKK – Sequence 1 Kinect v2
• PUTKK – Sequence 2 Kinect v1
• PUTKK – Sequence 2 Kinect v2
• PUTKK – Sequence 3 Kinect v1
• PUTKK – Sequence 3 Kinect v2
• PUTKK – Sequence 4 Kinect v1
• PUTKK – Sequence 4 Kinect v2

RGB camera video in PUTKK different speed sequences in youtube:

• PUTKK – Sequence 5 Kinect v1
• PUTKK – Sequence 5 Kinect v2
• PUTKK – Sequence 6 Kinect v1
• PUTKK – Sequence 6 Kinect v2
• PUTKK – Sequence 7 Kinect v1
• PUTKK – Sequence 7 Kinect v2
• PUTKK – Sequence 8 Kinect v1
• PUTKK – Sequence 8 Kinect v2

Scene reconstruction of PUTKK with FastFusion in youtube:

• PUTKK – Sequence 2 Kinect v1 – Scene reconstruction from ground truth
• PUTKK – Sequence 2 Kinect v2 – Scene reconstruction from ground truth