Mapping Indoor Spaces by Adaptive Coarse-to-Fine Registration of RGB-D Data

Santos, Daniel Rodrigues dos; Basso, Marcos Aurélio; Khoshelham, Kourosh; Oliveira, Elizeu de; Pavan, Nadisson Luis; Vosselman, G.

doi:10.1109/lgrs.2015.2508880

Cited by 36 publications

(26 citation statements)

References 17 publications

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“…In [19], a coarse registration of the RGB-D sequence was done using 3D points based on SIFT and depth measurements, where they carefully weighted the theoretical random error based on the novel disparity model. The work in [20] proposed an epipolar search method for point correspondence and defined the 3D point weights according to a theoretical random error of depth measurements.…”

Section: Related Workmentioning

confidence: 99%

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Globally Consistent Indoor Mapping via a Decoupling Rotation and Translation Algorithm Applied to RGB-D Camera Output

Liu

Wang

Song

et al. 2017

IJGI

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This paper presents a novel RGB-D 3D reconstruction algorithm for the indoor environment. The method can produce globally-consistent 3D maps for potential GIS applications. As the consumer RGB-D camera provides a noisy depth image, the proposed algorithm decouples the rotation and translation for a more robust camera pose estimation, which makes full use of the information, but also prevents inaccuracies caused by noisy depth measurements. The uncertainty in the image depth is not only related to the camera device, but also the environment; hence, a novel uncertainty model for depth measurements was developed using Gaussian mixture applied to multi-windows. The plane features in the indoor environment contain valuable information about the global structure, which can guide the convergence of camera pose solutions, and plane and feature point constraints are incorporated in the proposed optimization framework. The proposed method was validated using publicly-available RGB-D benchmarks and obtained good quality trajectory and 3D models, which are difficult for traditional 3D reconstruction algorithms.

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Section: Related Workmentioning

confidence: 99%

“…The full Jacobian matrix can be computed using Equation (19). The row of the full Jacobian matrix is a combination of all the object functions, and its columns comprise a mixture of all variables.…”

Section: Rotation Solvingmentioning

confidence: 99%

Globally Consistent Indoor Mapping via a Decoupling Rotation and Translation Algorithm Applied to RGB-D Camera Output

Liu

Wang

Song

et al. 2017

IJGI

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“…Based on the method of weighting the 3-D points, Santos et al (2016) introduced a refined mapping method, robust coarse-to-fine registration method. The loop-closure detection and a global adjustment of the frames sequences are used to improve the consistency of the frames sequences [20]. Endres et al (2014) applied a similar approach, using the RANSAC (RANdom Sample Consensus) method to estimate the transformations between associated key points, and then generated a volumetric 3D map of the environment [21].…”

Section: Literature Reviewmentioning

confidence: 99%

Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling

Tang

Zhu

et al. 2016

Sensors

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RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method.

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“…Nevertheless, the developed approach depends on additional sensors (i.e, IMU) to provide a good initial alignment for the ICP. Dos Santos et al (2016) presented an adaptive coarse-to-fine registration method for 3D indoor mapping using RGB-D data. They have weighted the 3D points based on the theoretical random error of depth measurements, such as in Khoshelham et al (2013)They also have introduced a novel disparity-based model for an accurate and robust coarse-to-fine registration.…”

Section: Related Workmentioning

confidence: 99%

“…Then, we realize an image normalization procedure in the RGB frame, and the epipolar geometry is used to transform the visual features to the 3D space (Dos Santos et al, 2016).…”

Section: D Point Matching Proceduresmentioning

confidence: 99%

A Weighted Closed-Form Solution for RGB-D Data Registration

Vestena¹,

Santos²,

Jr.³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.

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Mapping Indoor Spaces by Adaptive Coarse-to-Fine Registration of RGB-D Data

Cited by 36 publications

References 17 publications

Globally Consistent Indoor Mapping via a Decoupling Rotation and Translation Algorithm Applied to RGB-D Camera Output

Globally Consistent Indoor Mapping via a Decoupling Rotation and Translation Algorithm Applied to RGB-D Camera Output

Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling

A Weighted Closed-Form Solution for RGB-D Data Registration

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