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Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds [article]

Bowen Cheng, Lu Sheng, Shaoshuai Shi, Ming Yang, Dong Xu
2021 arXiv   pre-print
Inspired by the back-tracing strategy in the conventional Hough voting methods, in this work, we introduce a new 3D object detection method, named as Back-tracing Representative Points Network (BRNet),  ...  3D object detection in point clouds is a challenging vision task that benefits various applications for understanding the 3D visual world.  ...  for 3D object detection in point clouds 2 .  ... 
arXiv:2104.06114v2 fatcat:4plczfhjrfexhehiiawsktzqqe

Deep Hough Voting for 3D Object Detection in Point Clouds [article]

Charles R. Qi, Or Litany, Kaiming He, Leonidas J. Guibas
2019 arXiv   pre-print
Few works have attempted to directly detect objects in point clouds. In this work, we return to first principles to construct a 3D detection pipeline for point cloud data and as generic as possible.  ...  To address the challenge, we propose VoteNet, an end-to-end 3D object detection network based on a synergy of deep point set networks and Hough voting.  ...  We thank Daniel Huber, Justin Johnson, Georgia Gkioxari and Jitendra Malik for valuable discussions and feedback.  ... 
arXiv:1904.09664v2 fatcat:7lwvrvnklvetpf6ama326ieh3i

Automatic normal orientation in point clouds of building interiors [article]

Sebastian Ochmann, Reinhard Klein
2019 arXiv   pre-print
Many existing approaches for automatic orientation of normals on meshes or point clouds make severe assumptions on the input data or the topology of the underlying object which are not applicable to real-world  ...  In contrast, our approach is specifically tailored to the challenging case of unstructured indoor point cloud scans of multi-story, multi-room buildings.  ...  Acknowledgments This work was supported by the DFG projects KL 1142/11-1 (DFG Research Unit FOR 2535 Anticipating Human Behavior) and KL 1142/9-2 (DFG Research Unit FOR 1505 Mapping on Demand).  ... 
arXiv:1901.06487v2 fatcat:cso4vkx4bvcllgcwpwlm6ft3xm

RBGNet: Ray-based Grouping for 3D Object Detection [article]

Haiyang Wang, Shaoshuai Shi, Ze Yang, Rongyao Fang, Qi Qian, Hongsheng Li, Bernt Schiele, Liwei Wang
2022 arXiv   pre-print
In this paper, we propose the RBGNet framework, a voting-based 3D detector for accurate 3D object detection from point clouds.  ...  In order to learn better representations of object shape to enhance cluster features for predicting 3D boxes, we propose a ray-based feature grouping module, which aggregates the point-wise features on  ...  Finally, the aggregated features and cluster features are concatenated for 3D object detection. Back-Tracing. It is first formulated in [7] .  ... 
arXiv:2204.02251v1 fatcat:5h4akemozjhblggyrm3r4uz3xi

Local Grid Rendering Networks for 3D Object Detection in Point Clouds [article]

Jianan Li, Jiashi Feng
2020 arXiv   pre-print
The performance of 3D object detection models over point clouds highly depends on their capability of modeling local geometric patterns.  ...  We validate LGR-Net for 3D object detection on the challenging ScanNet and SUN RGB-D datasets.  ...  Point-based Models in 3D Object Detection Recent development of realtime applications such as autonomous driving and robotics has motivated increasing attention to 3D object detection in point clouds.  ... 
arXiv:2007.02099v1 fatcat:lvwyhxa2nnby7dghsxmsg5twci

MapSense

Mohamed Abdelaal, Suriya Sekar, Frank Dürr, Kurt Rothermel, Susanne Becker, Dieter Fritsch
2020 ACM Transactions on Internet of Things  
from a small set of crowd-sensed point clouds in an energy-efficient manner.  ...  To demonstrate the performance of MapSense, we implemented a crowdsensing Android App to collect 3D point clouds from two different buildings by six volunteers.  ...  ACKNOWLEDGMENT The authors would like to thank Lavinia Runceanu, for her help while collecting the mapping data.  ... 
doi:10.1145/3379342 dblp:journals/tiot/AbdelaalSDRBF20 fatcat:yovxy2thebd3ncmsg5n4xpsyee

Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes [article]

Yang You, Zelin Ye, Yujing Lou, Chengkun Li, Yong-Lu Li, Lizhuang Ma, Weiming Wang, Cewu Lu
2022 arXiv   pre-print
3D object detection has attracted much attention thanks to the advances in sensors and deep learning methods for point clouds.  ...  Finally, an LCC-aware back-projection checking algorithm iteratively cuts out bounding boxes from the generated vote maps, with the elimination of false positives.  ...  This work was also supported by the Shanghai AI development project (2020-RGZN-02006) and "cross research fund for translational medicine" of Shanghai Jiao Tong University (zh2018qnb17, zh2018qna37, YG2022ZD018  ... 
arXiv:2011.12001v3 fatcat:tmaqynytanby5kow3s7jzfbw3i

3D Moving Object Reconstruction by Temporal Accumulation

Anas Abuzaina, Mark S. Nixon, John N. Carter
2014 2014 22nd International Conference on Pattern Recognition  
We present a novel algorithm for full 3D reconstruction of unknown moving objects in 2.5D point cloud sequences, such as those generated by 3D sensors.  ...  Our algorithm incorporates structural and temporal motion information to build 3D models of moving objects and is based on motion compensated temporal accumulation.  ...  based on a computed space partitioning and votes for the best reconstruction based on the number of points in each resampled point cloud.  ... 
doi:10.1109/icpr.2014.370 dblp:conf/icpr/AbuzainaNC14 fatcat:ink2sqk2gfaotgehskwmm27jta

3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds

Lucía Díaz-Vilariño, Kourosh Khoshelham, Joaquín Martínez-Sánchez, Pedro Arias
2015 Sensors  
In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images.  ...  These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier  ...  Acknowledgments Authors would like to thank the Ministerio de Economía y Competitividad (Gobierno de España) for the financial support given through human resources grant (FPU AP2010-2969).  ... 
doi:10.3390/s150203491 pmid:25654723 pmcid:PMC4367370 fatcat:ezrfgibcqvbvjpyirgvi4bx4le

Scale-Invariant Vote-Based 3D Recognition and Registration from Point Clouds [chapter]

Minh-Tri Pham, Oliver J. Woodford, Frank Perbet, Atsuto Maki, Riccardo Gherardi, Björn Stenger, Roberto Cipolla
2013 Studies in Computational Intelligence  
This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time  ...  as well as with the commonly used Hough voting approach.  ...  Fig. 1 1 Our System for 3D-shape-based object recognition and registration. (a) Real object, fabricated from a CAD model. (b) Point cloud extracted using a multi-view stereo (MVS) system.  ... 
doi:10.1007/978-3-642-28661-2_6 fatcat:5zz7qksxqna7bbokgep3hesrca

3D piecewise planar object model for robotics manipulation

Johann Prankl, Michael Zillich, Markus Vincze
2011 2011 IEEE International Conference on Robotics and Automation  
This work presents automatic on-line 3D object model acquisition assuming a robot to manipulate the object. Objects are represented with piecewise planar surfaces in a spatiotemporal graph.  ...  Planes once detected in 2D are tracked and serve as priors in subsequent images. After reconstruction of the planes the 3D motion is analyzed and initial object hypotheses are created.  ...  Therefore we represent objects in a keyframe 2 based graph structure.  ... 
doi:10.1109/icra.2011.5979935 dblp:conf/icra/PranklZV11 fatcat:ygeurxwb7nfpjetpnyjw2oygoq

A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models

Rushikesh Battulwar, Masoud Zare-Naghadehi, Ebrahim Emami, Javad Sattarvand
2021 Journal of Rock Mechanics and Geotechnical Engineering  
We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.  ...  Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.  ...  National Institute for Occupational Safety and Health (NIOSH) under the Contract No. 75D30119C06044. We are grateful to the funding agency for their support.  ... 
doi:10.1016/j.jrmge.2021.01.008 fatcat:jo6mkqi22fbrhhlvf2ugj2vdqu

Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving [article]

Hanjiang Hu, Zuxin Liu, Sharad Chitlangia, Akhil Agnihotri, Ding Zhao
2022 arXiv   pre-print
Our results show that sensor placement is non-negligible in 3D point cloud-based object detection, which will contribute up to 10% performance discrepancy in terms of average precision in challenging 3D  ...  The code is available on https://github.com/HanjiangHu/Multi-LiDAR-Placement-for-3D-Detection.  ...  Deep hough voting for 3d object detection in point clouds.  ... 
arXiv:2105.00373v4 fatcat:xqwxkpbmrrcp3ecsewptsit3li

VoteHMR: Occlusion-Aware Voting Network for Robust 3D Human Mesh Recovery from Partial Point Clouds [article]

Guanze Liu, Yu Rong, Lu Sheng
2021 arXiv   pre-print
3D human mesh recovery from point clouds is essential for various tasks, including AR/VR and human behavior understanding.  ...  Previous works in this field either require high-quality 3D human scans or sequential point clouds, which cannot be easily applied to low-quality 3D scans captured by consumer-level depth sensors.  ...  Tracing Representative Points for Voting-Based 3D Object Detection in Point 2020.00530 Clouds.  ... 
arXiv:2110.08729v1 fatcat:3b25xw26qraalbtuuejmiqedwy

ARM3D: Attention-based relation module for indoor 3D object detection [article]

Yuqing Lan, Yao Duan, Chenyi Liu, Chenyang Zhu, Yueshan Xiong, Hui Huang, Kai Xu
2022 arXiv   pre-print
In the field of 3D object detection, previous methods have been taking the advantage of context encoding, graph embedding, or explicit relation reasoning to extract relation context.  ...  Inspired by recent attention mechanism like Transformer, we propose a novel 3D attention-based relation module (ARM3D).  ...  Related Work 3D object detection in point clouds. 3D object detection has been investigated for decades with numerous applications [4, 6, 18, 26, 31, 32, 38, 40, 53, 55, 56, 63, 65] .  ... 
arXiv:2202.09715v1 fatcat:t6t4mm37pbcyxhmh4pghjxinoq
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