Robust odometry estimation for RGB-D cameras

Kerl, Christian; Sturm, Jürgen; Cremers, Daniel

doi:10.1109/icra.2013.6631104

Cited by 483 publications

(413 citation statements)

References 32 publications

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“…For all the sequences, the performance of our approach was compared to the state-of-the-art method presented in [9]. We found that we achieve similar accuracy for small camera displacements, significantly outperforming [9] in the presence of wide baselines.…”

Section: Introductionmentioning

confidence: 99%

“…Odometry systems that operate with such information are, therefore, different from the monocular systems, since depth information can be explored for providing reliable camera poses and 3D reconstructions. Several researchers have focused on the problem of odometry and SLAM for RGD-D sensors [4,6,9,13,16]. Endres et al [4] proposed a two-fold SLAM system for RGBsensors.…”

Section: Related Workmentioning

confidence: 99%

“…Recently, odometry methods that take advantage of the depth and color information provided by RGB-D sensors have been developed [9,13]. They run in real-time and provide accurate estimations for high frame rate acquisitions and moderate sensor velocity.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Plane-based Odometry using an RGB-D Camera

Raposo¹,

Lourenço²,

Antunes³

et al. 2013

Procedings of the British Machine Vision Conference 2013

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Odometry consists in using data from a moving sensor to estimate change in position over time. It is a crucial step for several applications in robotics and computer vision. This paper presents a novel approach for estimating the relative motion between successive RGB-D frames that uses plane-primitives instead of point features. The planes in the scene are extracted and the motion estimation is cast as a plane-to-plane registration problem with a closed-form solution. Point features are only extracted in the cases where the plane surface configuration is insufficient to determine motion with no ambiguity. The initial estimate is refined in a photo-geometric optimization step that takes full advantage of the plane detection and simultaneous availability of depth and visual appearance cues. Extensive experiments show that our plane-based approach is as accurate as state-of-the-art point-based approaches when the camera displacement is small, and significantly outperforms them in case of wide-baseline and/or dynamic foreground.

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Section: Introductionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Plane-based Odometry using an RGB-D Camera

Raposo¹,

Lourenço²,

Antunes³

et al. 2013

Procedings of the British Machine Vision Conference 2013

View full text Add to dashboard Cite

show abstract

“…The sequences are labeled with 6-DOF ground truth from a motion capture system having 10 cameras. Six research publications about evaluating ego-motion estimation and SLAM over TUM Benchmark dataset are [21,38,45,84,86,87].…”

Section: Tum Benchmark Datasetmentioning

confidence: 99%

RGB-D datasets using microsoft kinect or similar sensors: a survey

Cai

Han

Liu

et al. 2016

Multimed Tools Appl

121

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RGB-D data has turned out to be a very useful representation of an indoor scene for solving fundamental computer vision problems. It takes the advantages of the color image that provides appearance information of an object and also the depth image that is immune to the variations in color, illumination, rotation angle and scale. With the invention of the low-cost Microsoft Kinect sensor, which was initially used for gaming and later became a popular device for computer vision, high quality RGB-D data can be acquired easily. In recent years, more and more RGB-D image/video datasets dedicated to various applications have become available, which are of great importance to benchmark the stateof-the-art. In this paper, we systematically survey popular RGB-D datasets for different applications including object recognition, scene classification, hand gesture recognition, 3D-simultaneous localization and mapping, and pose estimation. We provide the insights into the characteristics of each important dataset, and compare the popularity and the difficulty of those datasets. Overall, the main goal of this survey is to give a comprehensive description about the available RGB-D datasets and thus to guide researchers in the selection of suitable datasets for evaluating their algorithms.

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“…In their work, visual odometry was solved using a cost function which linearly combined sparse 2D image features and 3D points. Recently, Kerl et al (2013b) developed a probabilistic framework for RGB-D based visual odometry. Here, a photo-consistency error was measured between all pixels of consecutive images in order to compute the a-posteriori likelihood of the camera motion.…”

mentioning

confidence: 99%

Vision based persistent localization of a humanoid robot for locomotion tasks

Castelán

Arechavaleta

2016

International Journal of Applied Mathematics and Computer Science

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Typical monocular localization schemes involve a search for matches between reprojected 3D world points and 2D image features in order to estimate the absolute scale transformation between the camera and the world. Successfully calculating such transformation implies the existence of a good number of 3D points uniformly distributed as reprojected pixels around the image plane. This paper presents a method to control the march of a humanoid robot towards directions that are favorable for visual based localization. To this end, orthogonal diagonalization is performed on the covariance matrices of both sets of 3D world points and their 2D image reprojections. Experiments with the NAO humanoid platform show that our method provides persistence of localization, as the robot tends to walk towards directions that are desirable for successful localization. Additional tests demonstrate how the proposed approach can be incorporated into a control scheme that considers reaching a target position.

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Robust odometry estimation for RGB-D cameras

Cited by 483 publications

References 32 publications

Plane-based Odometry using an RGB-D Camera

Plane-based Odometry using an RGB-D Camera

RGB-D datasets using microsoft kinect or similar sensors: a survey

Vision based persistent localization of a humanoid robot for locomotion tasks

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