Towards a benchmark for RGB-D SLAM evaluation

نویسندگان

  • Jürgen Sturm
  • Stéphane Magnenat
  • Nikolas Engelhard
  • François Pomerleau
  • Francis Colas
  • Daniel Cremers
  • Roland Siegwart
  • Wolfram Burgard
چکیده

We provide a large dataset containing RGB-D image sequences and the ground-truth camera trajectories with the goal to establish a benchmark for the evaluation of visual SLAM systems. Our dataset contains the color and depth images of a Microsoft Kinect sensor and the groundtruth trajectory of camera poses. The data was recorded at full frame rate (30 Hz) and sensor resolution (640x480). The ground-truth trajectory was obtained from a high-accuracy motion-capture system with eight high-speed tracking cameras (100 Hz). Further, we provide the accelerometer data from the Kinect. Finally, we propose an evaluation criterion for measuring the quality of the estimated camera trajectory of visual SLAM systems.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Outdoor RGB-D SLAM Performance in Slow Mine Detection

The introduction of Kinect-style RGB-D cameras has dramatically revolutionized robotics research in a very short span. However, despite their low cost and excellent indoor performance in comparison with other competing technologies, they face some basic limitations which prevent their use in outdoor environments. Perhaps for the first time, we report an outdoor application of Kinect-style camer...

متن کامل

Loop Closing Detection in RGB-D SLAM Combining Appearance and Geometric Constraints

A kind of multi feature points matching algorithm fusing local geometric constraints is proposed for the purpose of quickly loop closing detection in RGB-D Simultaneous Localization and Mapping (SLAM). The visual feature is encoded with BRAND (binary robust appearance and normals descriptor), which efficiently combines appearance and geometric shape information from RGB-D images. Furthermore, t...

متن کامل

Robust Keyframe-based Dense SLAM with an RGB-D Camera

In this paper, we present RKD-SLAM, a robust keyframe-based dense SLAM approach for an RGB-D camera that can robustly handle fast motion and dense loop closure, and run without time limitation in a moderate size scene. It not only can be used to scan high-quality 3D models, but also can satisfy the demand of VR and AR applications. First, we combine color and depth information to construct a ve...

متن کامل

Evaluating Egomotion and Structure-from-Motion Approaches Using the TUM RGB-D Benchmark

In this paper, we present the TUM RGB-D benchmark for visual odometry and SLAM evaluation and report on the first use-cases and users of it outside our own group. The benchmark contains a large set of image sequences recorded from a Microsoft Kinect associated with highly accurate and time-synchronized ground truth camera poses from an external motion capture system. The dataset consists in tot...

متن کامل

Online 3D Reconstruction and 6-DoF Pose Estimation for RGB-D Sensors

In this paper, we propose an approach to Simultaneous Localization and Mapping (SLAM) for RGB-D sensors. Our system computes 6-DoF pose and sparse feature map of the environment. We propose a novel keyframe selection scheme based on the Fisher information, and new loop closing method that utilizes feature-to-landmark correspondences inspired by image-based localization. As a result, the system ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011