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Object pose estimation is frequently achieved by first segmenting an RGB image and then, given depth data, registering the corresponding point cloud segment against the object's 3D model.
Generalizing the hough transform to detect arbitrary shapes
Dana H Ballard · 1981
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Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
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Method for Registration of 3D Shapes
P. J. Besl and N. D. McKay · 1992
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Combinatorial and Experimental Results for Randomized Point Matching Algorithms
S. Irani and P. Raghavan · 1996
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Using spin images for efficient object recognition in cluttered 3d scenes
Andrew E. Johnson and Martial Hebert · 1999
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Object Recognition from Local Scale-Invariant Features
D. G. Lowe · 1999
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Determinantal Random Point Fields
A. Soshnikov · 2000
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Efficient Variants of the ICP Algorithm
S. Rusinkiewicz and M. Levoy · 2001
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Registration of Point Cloud Data from a Geometric Optimization Perspective
N. Mitra, N. Gelfand, H. Pottmann, and H. Guibas · 2004
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Robust Global Registration
N. Gelfand, N. Mitra, L. Guibas, and H. Pottmann · 2005
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3D Object Modeling and Recognition using Local Affine-Invariant Image Descriptors and Multi-view Spatial Constraints
F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce · 2006
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4-points Congruent Sets for Robust Pairwise Surface Registration
D. Aiger, N. J. Mitra, and D. Cohen-Or · 2008
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Fast point feature histograms (fpfh) for 3d registration
Radu Bogdan Rusu, Nico Blodow, and Michael Beetz · 2009
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Generalized-ICP
A. Segal, D. Haehnel, and S. Thrun · 2009
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Model Globally, Match Locally: Efficient and Robust 3D Object Recognition
B. Drost, M. Ulrich, N. Navab, and S. Ilic · 2010
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Unique signatures of histograms for local surface description
Federico Tombari, Samuele Salti, and Luigi Di Stefano · 2010
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The MOPED framework: Object Recognition and Pose Estimation for Manipulation
A. Collet, M. Martinez, and S. Srinivasa · 2011
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3d object recognition in range images using visibility context
Eunyoung Kim and Gerard Medioni · 2011
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Tutorial: Point cloud library: Three-dimensional object recognition and 6 dof pose estimation
A. Aldoma, Z.-C. Marton, F. Tombari, W. Wohlkinger, C. Potthast, B. Zeisl, R. B. Rusu, S. Gedikli, and M. Vincze · 2012
Cited alongside, same era.
3d pose estimation of daily objects using an rgb-d camera
Changhyun Choi and Henrik I Christensen · 2012
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3D Object Detection and Localization using Multimodal Point Pair Features
Analysis and Observations From the First Amazon Picking Challenge
N. Correll, K. E. Bekris, D. Berenson, O. Brock, A. Causo, K. Hauser, K. Osada, A. Rodriguez, J. Romano, and P. Wurman · 2016
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Synthesizing Training Data for Object Detection in Indoor Scenes
G. Georgakis, A. Mousavian, A. C. Berg, and J. Kosecká · 2016
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Team delft’s robot winner of the amazon picking challenge 2016
Carlos Hernandez, Mukunda Bharatheesha, Wilson Ko, Hans Gaiser, Jethro Tan, Kanter van Deurzen, Maarten de Vries, Bas Van Mil, Jeff van Egmond, Ruben Burger, et al · 2016
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Going further with point pair features
Stefan Hinterstoisser, Vincent Lepetit, Naresh Rajkumar, and Kurt Konolige · 2016
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Discriminatively-guided Deliberative Perceptino for Pose Estimation of Multiple 3D Object Instances
V. Narayanan and M. Likhachev · 2016
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B. Drost and S. Ilic · 2012
Cited alongside, same era.
Sparse Iterative Closest Point
S. Bouazix, A. Tagliasacchi, and M. Pauly · 2013
Cited alongside, same era.
Supermatching: Feature Matching using Supersymmetric Geometric Constraints
Z.-Q. Cheng, Y. Chen, R. Martin, Y.-K. Lai, and A. Wang · 2013
Cited alongside, same era.
Learning 6d object pose estimation using 3d object coordinates
Eric Brachmann, Alexander Krull, Frank Michel, Stefan Gumhold, Jamie Shotton, and Carsten Rother · 2014
Cited alongside, same era.
Super4PCS Fast Global Pointcloud Registration via Smart Indexing
N. Mellado, D. Aiger, and N. J. Mitra · 2014
Cited alongside, same era.
Latent-class Hough Forests for 3D Object Detection and Pose Estimation
A. Tejani, D. Tang, R. Kouskouridas, and T. K. Kim · 2014
Cited alongside, same era.
Point pair features based object detection and pose estimation revisited
Tolga Birdal and Slobodan Ilic · 2015
Cited alongside, same era.
Berk Calli, Arjun Singh, James Bruce, Aaron Walsman, Kurt Konolige, Siddhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar · 2017
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V4pcs: Volumetric 4pcs algorithm for global registration
Jida Huang, Tsz-Ho Kwok, and Chi Zhou · 2017
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Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again
Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic, and Nassir Navab · 2017
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Global hypothesis generation for 6d object pose estimation
Frank Michel, Alexander Kirillov, Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, and Carsten Rother · 2017
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A self-supervised learning system for object detection using physics simulation and multi-view pose estimation
Chaitanya Mitash, Kostas E Bekris, and Abdeslam Boularias · 2017
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Seeing Glassware: from Edge Detection to Pose Estimation and Shapre Recovery
C. J. Phillips, M. Lecce, and K. Daniilidis · 2017
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Sparse Point Registration
R. A. Srivatsan, P. Vagdargi, and H. Choset · 2017
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Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge
A. Zeng, K.-T. Yu, S. Song, D. Suo, E. Walker Jr, A. Rodriguez, and J. Xiao · 2017
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Improving 6d pose estimation of objects in clutter via physics-aware monte carlo tree search
Chaitanya Mitash, Abdeslam Boularias, and Kostas E Bekris · 2018
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PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, and Dieter Fox · 2018
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