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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Monene-Theriault, Hugues Cretu, Ana-Maria Payeur, Pierre Univ Quebec Outaouais Dept Comp Sci & Engn Gatineau PQ Canada Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (纸本)9781479938407

The paper proposes an automated method for the modeling of objects using multiple discrete levels of detail for virtual reality applications. The method combines classical discrete level of detail approaches with a novel solution for the creation of selectively-densified object meshes. A neural gas network is used to capture regions of interest over a sparse point cloud representing a 3d object. Meshes at different resolutions that preserve these regions are then constructed by adapting a classical simplification algorithm to allow the simplification process to affect only the regions of lower interest. different interest point detectors are incorporated in a similar manner and compared with the proposed approach. A novel solution based on learning is proposed to select the number of faces for the discrete models of an object at different resolutions.

关键词： interest points 3d object modeling level of detail selectively-densified surface mesh

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Fast 3d-object modeling with Kinect and Rotation Platform 3

Fast 3D-Object Modeling with Kinect and Rotation Platform

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International Conference on Robot Vision and Signal Processing

作者： Xu, Huarong Wang, Xiaoming Shi, Limin Xiamen Univ Technol Dept Comp Sci & Technol Xiamen Peoples R China Shandong Jiaotong Univ Dept Math & Phys Jinan Peoples R China Chinese Acad Sci Inst Automat Res Ctr Aerosp Informat Beijing Peoples R China

ISBN: (纸本)9781467396462

High-fidelity reconstruction of complete objects is known as a particularly challenging problem. In this paper, we report a system for object modeling by Kinect and rotation platform. Our modeling solution is divided into three steps: (1) system calibration;(2) Point clouds real time registration;(3) Mesh surface reconstruction and automatic texture mapping. We propose an easy-to-use calibration method for the first step, and based on the calibration result, an automated texture-independent 3d point clouds registration method is presented. Finally, triangulate meshing and automated texture mapping technique are used to recreate complete mesh model from the integrated point clouds. Our system is validated by modeling several real-world objects, and all the results show its effectiveness.

关键词： 3d object modeling Kinect rotation platform weak tecture

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3d object modeling with Neural Gas Based Selective densification of Surface Meshes

3D Object Modeling with Neural Gas Based Selective Densifica...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Hugues Monette-Theriault Ana-Maria Cretu Pierre Payeur Department of Computer Science and Engineering Universite du Quebec en Outaouais School of Electrical Engineering and Computer Science University of Ottawa

ISBN: (纸本)9781479938414

关键词： Interest points 3d object modeling Level of detail Selectively-densified surface mesh

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Bilateral Coarse-to-Fine Network for Point Cloud Completion 48

Bilateral Coarse-to-Fine Network for Point Cloud Completion

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Phong Nguyen, Tran Thanh Lam Phung, Son Gopaldasani, Vinod Whitelaw, Jane University of Wollongong NSW Australia

ISBN: (纸本)9781728163277

Point cloud completion aims to accurately estimate complete point clouds from partial observations. Existing methods of-ten directly infer the missing points from the partial shape, but they suffer from limited structural information. To address this, we propose the Bilateral Coarse-to-Fine Network (BCF-Net), which leverages 2d images as guidance to compensate for structural information loss. Our method introduces a multi-level codeword skip-connection to estimate structural details. Experimental results show that BCF-Net outperforms state-of-the-art point cloud completion networks on synthetic and real-world datasets. © 2023 IEEE.

关键词： 3d object modeling bilateral filtering image guidance Point cloud completion

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Acquisition and Neural Network Prediction of 3d deformable object Shape Using a Kinect and a Force-Torque Sensor

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SENSORS 2017年第5期17卷 1083-1083页

作者： Tawbe, Bilal Cretu, Ana-Maria Univ Quebec Outaouais Dept Comp Sci & Engn Gatineau PQ J8X 3X7 Canada

The realistic representation of deformations is still an active area of research, especially for deformable objects whose behavior cannot be simply described in terms of elasticity parameters. This paper proposes a data-driven neural-network-based approach for capturing implicitly and predicting the deformations of an object subject to external forces. Visual data, in the form of 3d point clouds gathered by a Kinect sensor, is collected over an object while forces are exerted by means of the probing tip of a force-torque sensor. A novel approach based on neural gas fitting is proposed to describe the particularities of a deformation over the selectively simplified 3d surface of the object, without requiring knowledge of the object material. An alignment procedure, a distance-based clustering, and inspiration from stratified sampling support this process. The resulting representation is denser in the region of the deformation (an average of 96.6% perceptual similarity with the collected data in the deformed area), while still preserving the object's overall shape (86% similarity over the entire surface) and only using on average of 40% of the number of vertices in the mesh. A series of feedforward neural networks is then trained to predict the mapping between the force parameters characterizing the interaction with the object and the change in the object shape, as captured by the fitted neural gas nodes. This series of networks allows for the prediction of the deformation of an object when subject to unknown interactions.

关键词： deformation force-torque sensor Kinect iterative closest point neural gas neural networks clustering mesh simplification RGB-d data 3d object modeling

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Indoor objects 3d modeling Based on RGB-d Camera for Robot Vision 7

Indoor Objects 3D Modeling Based on RGB-D Camera for Robot V...

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International Conference on Fluid Power and Mechatronics FPM

作者： Shi, Guangsheng Zhao, Lijun Wang, Ke Gao, Yunfeng Liu, Yihuan Harbin Inst Technol State Key Lab Robot & Syst Harbin Peoples R China

ISBN: (纸本)9781479987702

The3d-object modeling hasbecome one hottopic in robot vision field for robots locating, grabbing and dropping operation. In this paper, we propose anefficient method of object modeling based RGB-d camera (Kinect) that can help the robot to carry out operation task. Our method is divided into three stage: firstly, point clouds of scene containing object are captured from thecamera and plane-segmentation to extract clusters of object;secondly, the preprocessed method is used to filter noise and outlier points;Points pair-wise alignment by way of our proposed pairs rejection strategy, global consistent alignment of the complete object and object-centered representation easy to manipulate. Besides, for the well-known loop closure problem, we optimize the pose and eliminate the accumulations base on the ICP improved algorithm. Finally, the proposed method is validated by the modeling of several household objects.

关键词： ICP 3d object modeling noise reduction loop optimization

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Effortless Scanning of 3d object Models by Boundary Aligning and Stitching

Effortless Scanning of 3D Object Models by Boundary Aligning...

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9th International Conference on Computer Vision Theory and Applications (VISAPP)

作者： Brandao, Susana Costeira, Joao P. Veloso, Manuela Univ Lisbon Inst Super Tecn Av Rovisco Pais Lisbon Portugal Carnegie Mellon Univ Elect & Comp Engn Dept Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Comp Sci Pittsburgh PA 15213 USA

ISBN: (纸本)9789897581335

We contribute a novel algorithm for the digitation of complete 3d object models that requires little preparation effort from the user. Notably, the presented algorithm, Joint Alignment and Stitching of Non-Overlapping Meshes (JASNOM), completes 3d object models by aligning and stitching two 3d meshes by the boundaries and does not require any previous registration between them. JASNOM only requirement is the lack of overlap between meshes, which is simple to achieve in most man made object. JASNOM takes advantage that both meshes can only be connected by their boundary to reframe the alignment problem as a search of the best assignment between boundary vertices. To make the problem tractable, JASNOM reduces the search space considerably by imposing strong constraints on valid assignments that transform the original combinatorial problem into a discrete linear problem. By not requiring previous camera registration and by not depending on shape features, JASNOM contributions range from quick modeling of 3d objects to hole filling in meshes.

关键词： 3d object modeling

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Rapid 3d object detection and modeling using range data from 3d range imaging camera for heavy equipment operation

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AUTOMATION IN CONSTRUCTION 2010年第7期19卷 898-906页

作者： Son, Hyojoo Kim, Changwan Choi, Kwangnam Chung Ang Univ Dept Architectural Engn Seoul 156756 South Korea Chung Ang Univ Dept Comp Sci & Engn Seoul 156756 South Korea

Automated detection and modeling of 3d objects located in a construction work environment is critical for autonomous heavy equipment operation. Such automation allows for accurate, efficient, and autonomous operation of heavy equipment in a broad range of construction tasks by providing interactive background information. This paper proposes a 3d object detection and modeling system which utilizes range data obtained by 3d range imaging camera to generate 3d object models with an acceptable level of accuracy in a few seconds. The proposed system consists of four steps: data acquisition, pre-processing, object segmentation, and 3d model generation. The system was tested on the modeling of different classes of construction objects on actual construction sites. The results show that the proposed 3d object detection and modeling system achieves a good balance between speed and accuracy, and hence could be used to enhance efficiency and productivity in the autonomous operation of heavy equipment (C) 2010 Elsevier B.V. All rights reserved.

关键词： 3d object detection 3d object modeling 3d range imaging camera Range data Heavy equipment operation Construction automation

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Indoor objects 3d modeling Based on RGB-d Camera for Robot Vision

Indoor Objects 3D Modeling Based on RGB-D Camera for Robot V...

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2015 International Conference on Fluid Power and Mechatronics

作者： Guangsheng Shi Lijun Zhao Ke Wang Yunfeng Gao Yihuan Liu State key laboratory of robotics and system Harbin Institute of Technology

The 3d-object modeling hasbecome one hottopic in robot vision field for robots locating, grabbing and dropping operation. In this paper, we propose anefficient method of object modeling based RGB-d camera(Kinect) that can help the robot to carry out operation task. Our method is divided into three stage: firstly, point clouds of scene containing object are captured from thecamera and plane-segmentation to extract clusters of object;secondly, the preprocessed method is used to filter noise and outlier points;Points pair-wise alignment by way of our proposed pairs rejection strategy, global consistent alignment of the complete object and object-centered representation easy to manipulate. Besides, for the well-known loop closure problem, we optimize the pose and eliminate the accumulations base on the ICP improved algorithm. Finally, the proposed method is validated by the modeling of several household objects.

关键词： ICP 3d object modeling noise reduction loop optimization

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Interaction with Virtual Spiders for Eliciting disgust in the Treatment of Phobias

Interaction with Virtual Spiders for Eliciting Disgust in th...

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IEEE International Symposium on Haptic, Audio and Visual Environments and Games (HAVE)

作者： Cavrag, Miroslav Lariviere, Guillaume Cretu, Ana-Maria Bouchard, Stephane Univ Quebec Outaouais Dept Comp Sci & Engn Quebec City PQ Canada Univ Quebec Outaouais Cyberpsychol Lab Dept Psychoeduc & Psychol Quebec City PQ Canada

ISBN: (纸本)9781479959648

Virtual reality has already been successfully used as a therapeutic tool for the treatment of various phobias. due to advances in the 3d graphics and in the computing power, the real-time visual rendering of a virtual world poses no significant problems nowadays. However, the haptic interaction with such environments remains a challenge. This paper explores the haptic interaction with a dedicated virtual environment in spider phobia treatment to elicit disgust, as changes in fear and in disgust were shown to be highly associated with the observed decline in arachnophobic symptoms. A dedicated virtual environment is programmed within which a Novint Falcon haptic device is used for the interaction with a virtual spider. different software options for interfacing with the haptic device and for the modeling of 3d objects are compared and discussed. Three testing scenarios are implemented that allow a subject to be gradually exposed to his/her spider phobia.

关键词： virtual reality haptic interaction 3d object modeling phobia treatment

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