Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid

By Gary Kwok-Leung Tam, Zhi-Quan Cheng, Yu-Kun Lai, Frank C. Langbein, Yonghuai Liu, A. David Marshall, Ralph Robert Martin, Xianfang Sun, Paul L. Rosin. IEEE Transactions on Visualization and Computer Graphics, 2013

715 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Geology

View Paper: https://www.semanticscholar.org/paper/78f2ecd259252386754729c7205ed8c70f0dabac

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Yu Xiang
2. Heng Yang
3. Augusto Salazar
4. Dylan Campbell
5. Dieter Fox
6. Yuxin Yao
7. Luca Carlone
8. Jeffrey F. Cohn

In Computer Graphics and Computer-Aided Design

1. Yuxin Yao
2. Juyong Zhang
3. Bailin Deng
4. Heng Yang
5. Dylan Campbell
6. Dieter Fox
7. Luca Carlone
8. Timo Bolkart

In Geology

1. Heng Yang
2. Yu Xiang
3. Dylan Campbell
4. Dieter Fox
5. Yuxin Yao
6. Luca Carlone
7. Juyong Zhang
8. Jiaolong Yang

Citations in the corpus

• Multilinear Wavelets: A Statistical Shape Space for Human Faces (2014, background): “Computing correspondences between a set of shapes is a challenging problem in general [27].”
• Fast and Robust Iterative Closest Point (2020, background): “For a comprehensive review of rigid and nonrigd registration, the reader is referred to [14], [15].”
• 3D Morphable Face Models—Past, Present, and Future (2019, neutral): “Many methods exist to establish point-to-point correspondence for general classes of objects (e.g., [Tam et al. 2013; van Kaick et al. 2011]), yet the space of face deformations is strongly constrained.”
• Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration (2016, background): “For other papers, the reader is referred to two surveys on ICP variants [6], [25], a recent survey on 3D point cloud and mesh registration [26], an overview of 3D registration [27] and the references therein.”
• Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-related Applications (2016, methodology): “For RGB images , Viola&Jones [60] still is one of the most used algorithms [10], [61], [177].”
• Review of statistical shape spaces for 3D data with comparative analysis for human faces (2012, methodology): “We refer the reader to recent surveys [3, 4] for more information.”
• Colored Point Cloud Registration Revisited (2017, neutral): “Its variants have been extensively studied [31, 33, 38].”
• Fast Global Registration (2016, neutral): “Geometric registration has been extensively studied [15, 28, 36, 38].”
• The role of RGB-D benchmark datasets: an overview (2013, background): “Highly accurate depth data are necessary for 3D reconstruction and simultaneous reconstruction and simulta- neous localization and mapping (SLAM) applications, although the requirements for mapping or localization can differ within the applicational context.”
• DeepIM: Deep Iterative Matching for 6D Pose Estimation (2018, methodology): “The most well-known local refinement algorithm is the Iterative Closest Point (ICP) algorithm (Besl and McKay, 1992) and its variants (Rusinkiewicz and Levoy, 2001; Salvi et al., 2007; Tam et al., 2013).”
• TEASER: Fast and Certifiable Point Cloud Registration (2020, background): “It finds applications in motion estimation and 3-D reconstruction [3]–[6], object recognition and localization [7]–[10], panorama stitching [11], and medical imaging [12], [13], to name a few.”