Multiscale Sparse Features Embedded 4-Points Congruent Sets for Global Registration of TLS Point Clouds

Xu, Zhihua; Xu, Ershuai; Zhang, Zhenxin; Wu, Lixin

doi:10.1109/lgrs.2018.2872353

Cited by 31 publications

(14 citation statements)

References 24 publications

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“…Authors of other works separate the process into a coarse and a fine registration [29], [30]. Moreover, the 4-Points Congruent Sets (4PCS) techniques are very popular, especially for global registration strategies [31]- [33] such as algorithms based on RANdom SAmple Consensus (RANSAC) [34]- [36]. Other related works try to find representative local or global features that are used…”

Section: Previous Workmentioning

confidence: 99%

Broad-to-Narrow Registration and Identification of 3D Objects in Partially Scanned and Cluttered Point Clouds

Arvanitis

Zacharaki

Váša

et al. 2022

IEEE Trans. Multimedia

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The new generation 3D scanner devices have revolutionized the way information from 3D objects is acquired, making the process of scene capturing and digitization straightforward. However, the effectiveness and robustness of conventional algorithms for real scene analysis are usually deteriorated due to challenging conditions, such as noise, low resolution, and bad perceptual quality. In this work, we present a methodology for identifying and registering partially-scanned and noisy 3D objects, lying in arbitrary positions in a 3D scene, with corresponding high-quality models. The methodology is assessed on point cloud scenes with multiple objects with large missing parts. The proposed approach does not require connectivity information and is thus generic and computationally efficient, thereby facilitating computationally demanding applications, like augmented reality. The main contributions of this work are the introduction of a layered joint registration and indexing scheme of cluttered partial point clouds using a novel multi-scale saliency extraction technique to identify distinctive regions, and an enhanced similarity criterion for object-to-model matching. The processing time of the process is also accelerated through 3D scene segmentation. Comparisons of the proposed methodology with other state-of-the-art approaches highlight its superiority under challenging conditions.

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Section: Previous Workmentioning

confidence: 99%

Broad-to-Narrow Registration and Identification of 3D Objects in Partially Scanned and Cluttered Point Clouds

Arvanitis

Zacharaki

Váša

et al. 2022

IEEE Trans. Multimedia

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“…Huang et al [30] proposed Volumetric 4PCS(V4PCS), which incorporated the volumetric information to the S4PCS to accelerate the extraction of the congruent bases. The MSSF-4PCS, proposed by Xu et al [17], embedded multiscale sparse features (MSSF) with sparse coding into 4PCS to enable efficient global registration of point clouds.…”

Section: Related Workmentioning

confidence: 99%

Global Adaptive 4-Points Congruent Sets Registration for 3D Indoor Scenes With Robust Estimation

Sun

Zhang

et al. 2020

IEEE Access

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As a powerful global registration method for point clouds, the 4-points congruent sets (4PCS) algorithm has been wildly used in the 3D scene reconstruction field. In this paper, we propose an adaptive 4PCS (A4PCS), which aims to provide a robustness rigid transformation for two or more overlapping laser scans. The proposed method only incorporates the distance information of the stereoscopic base set and a fast mechanism for congruent base extraction into 4PCS. To ensure the registration accuracy when dealing with restrictive situations, such as point clouds with small overlaps or scenes with symmetrical structures, a non-coplanar 4-points base set is adopted without extra time consumption. Besides, the adaptive set finetuning is introduced to the point pair searching process to accelerate the convergence of the algorithm. In addition, we replace the binary cost function of the original 4PCS with a modified estimator to strengthen the robustness of the proposed method. Experiments on thirteen pairs of point clouds for 3D indoor scenes, including ten regular size models and three scenes of one large-scale model, can demonstrate the accuracy and efficiency of the proposed method. INDEX TERMS Global registration, 4-points congruent sets (4PCS), rigid transformation, point clouds.

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“…We adopted normal constraints to remove the redundant 4-point bases that exist in a plane surface, to improve the efficiency and robustness [40].…”

Section: Of 17mentioning

confidence: 99%

“…To solve this issue, we considered the similarity of multi-scale features between the two sets of 3D neighborhood points that centered at the approximate 4PCS, from the different TLS surveys. Following the strategy in [40], we extracted the point features [49][50][51], at three scales, i.e., r, r + r, and r + 2 r, where r is a predefined search radius, and r is a scale interval. This configuration enabled us to handle the problems associated with various point densities and noise.…”

Section: Coarse Registration Of Temporal Tls Surveys By Matching Multmentioning

confidence: 99%

“…Differing from the existing study in [40], which collected the most congruent 4-point sets, we identified all the matches from the 3D neighbor point sets centered at the approximated 4PCS. Let p 1 ∈ J and q 1 ∈ S be a pair of approximate congruent points from two temporal TLS surveys, where Adj(p 1 ) and Adj(q 1 ) are the corresponding 3D neighbors centered at p 1 and q 1 , respectively.…”

Section: Coarse Registration Of Temporal Tls Surveys By Matching Multmentioning

confidence: 99%

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Registration of Terrestrial Laser Scanning Surveys Using Terrain-Invariant Regions for Measuring Exploitative Volumes over Open-Pit Mines

et al. 2019

Remote Sensing

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Terrestrial laser scanning (TLS) techniques have been widely used in open-pit mine applications. It is a crucial task to measure the exploitative volume of open-pit mines, within a specific time interval. One major challenge is posed, however, when conducting accurate registrations for temporal TLS surveys in continuously changing areas, created by excavation activities. In this paper, we propose a coarse-to-fine registration method, based on terrain-invariant regions (TIR), for temporal TLS surveys. More specifically, an approximate four-point congruent set (4PCS) of temporal TLS surveys is first identified, based on affine invariant rules. Second, a set of correspondences among temporal TLS surveys were collected by matching multi-scale sparse features of the 3D neighbors, centered at the approximate 4PCS. Third, the correspondences were used to estimate a rigid motion between the overlapping TLS surveys for the coarse registration, according to which the initial TIR from temporal TLS surveys were identified. Finally, the rigid motion between temporal TLS was iteratively optimized, based on the point clouds, only from the TIR. Based on the fine-level registered TLS surveys, Digital Elevation Models (DEMs) can be generated to calculate the exploitative volume, through a DEM differential. We applied the proposed method to two open-pit mines in China, and also compared our method with five state-of-the-art methods for registering temporal TLS surveys. Experimental results indicated that the proposed method achieved a higher registration accuracy than the state-of-the-art methods. Based on the registered result, our method achieved a 98.03% overall accuracy for measuring the exploitative volume, compared to in-situ measurement.

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Multiscale Sparse Features Embedded 4-Points Congruent Sets for Global Registration of TLS Point Clouds

Cited by 31 publications

References 24 publications

Broad-to-Narrow Registration and Identification of 3D Objects in Partially Scanned and Cluttered Point Clouds

Broad-to-Narrow Registration and Identification of 3D Objects in Partially Scanned and Cluttered Point Clouds

Global Adaptive 4-Points Congruent Sets Registration for 3D Indoor Scenes With Robust Estimation

Registration of Terrestrial Laser Scanning Surveys Using Terrain-Invariant Regions for Measuring Exploitative Volumes over Open-Pit Mines

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