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检索条件"任意字段=International Symposium on 3D Data Processing Visualization and Transmission"

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Training-Based Object Recognition in Cluttered 3d Point Clouds

Training-Based Object Recognition in Cluttered 3D Point Clou...

引用

international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Guan Pang Ulrich Neumann Department of Computer Science University of Southern California Los Angeles CA USA

Recognition of three dimensional (3d) objects is a challenging problem, especially in cluttered or occluded scenes. Many existing methods focus on a specific type of object or scene, or require prior segmentation. We describe a robust and efficient general purpose 3d object recognition method that combines machine learning procedures with 3d local features, without a requirement for a priori object segmentation. Experiments validate our method on various object types from engineering and street data scans.

关键词： Three-dimensional displays Training detectors Object recognition Shape Feature extraction Valves

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3d Face Template Registration Using Normal Maps

3D Face Template Registration Using Normal Maps

引用

international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Zhongjie Wang Martin Grochulla Thorsten Thormählen Hans-Peter Seidel MPI Informatik Saarbrucken Germany Philipps University of Marburg Marburg Germany

This paper presents a semi-automatic method to fit a template mesh to high-resolution normal data, which is generated using spherical gradient illuminations in a light stage. Template fitting is an important step to build a 3d morph able face model, which can be employed for image-Based facial performance capturing. In contrast to existing 3d reconstruction approaches, we omit the structured light scanning step to obtain low-frequency 3d information and rely solely on normal data from multiple views. This reduces the acquisition time by over 50 percent. In our experiments the proposed algorithm is successfully applied to real faces of several subjects. Experiments with synthetic data show that the fitted face template can closely resemble the ground truth geometry.

关键词： Three-dimensional displays Face Cameras Optimization Lighting Shape Solid modeling

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Multi-level Information Representation Based LOd Streaming for Urban Navigation

Multi-level Information Representation Based LOD Streaming f...

引用

international symposium on Ubiquitous Virtual Reality, ISUVR

作者： J. divya Udayan Hyungseok Kim Jun Lee Jee-In-Kim Keetae Kim Dept. of Internet & Multimedia Engineering Konkuk University Republic of Korea Daum Corporation Republic of Korea

Streaming of 3d data sets is a key technology for remote rendering and visualization of huge and complex geometrical models like large scale city models. Even with high speed network it is still difficult to share the 3d information of a city scene among different users. In our work, we have devised a new data representation mechanism and transmission scheme to render the 3d models with less content and less computational cost. Our approach uses light weight building geometry and multi-level textured LOd representation to transmit data via streaming. In addition, we suggest a technique for rendering with selective LOds by emphasizing the regions of interest (ROIs) depending on the importance of the building for a specific user. The LOd distribution is updated over the ROI as the gaze point of the viewer moves over the model surfaces. Preliminary tests and evaluations reveal the feasibility of our method to be extended to large scale mobile applications.

关键词： Buildings Three-dimensional displays Navigation Cities and towns Solid modeling Computational modeling data models

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Augmented Motion History Volume for Spatiotemporal Editing of 3d Video in Multi-party Interaction Scenes

Augmented Motion History Volume for Spatiotemporal Editing o...

引用

international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Qun Shi Shohei Nobuhara Takashi Matsuyama Department of Intelligence Science and Technology Graduate School of Informatics Kyoto University Kyoto Japan

In this paper we present a novel method that performs spatiotemporal editing of 3d multi-party interaction scenes for free-viewpoint browsing, from separately captured data. The main idea is to first propose the augmented Motion History Volume (aMHV) for motion representation. Then by modeling the correlations between different aMHVs we can define a multi-party interaction dictionary, describing the spatiotemporal constraints for different types of multiparty interaction events. Finally, constraint satisfaction and global optimization methods are proposed to synthesize natural and continuous multi-party interaction scenes. Experiments with real data illustrate the effectiveness of our method.

关键词： Motion segmentation Spatiotemporal phenomena Three-dimensional displays dictionaries History Computational modeling Kinematics

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Online Building Segmentation from Ground-Based LidAR data in Urban Scenes

Online Building Segmentation from Ground-Based LiDAR Data in...

引用

international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Jizhou Gao Ruigang Yang University of Kentucky USA

The availability of active 3d sensing devices such as LidAR has significantly increased the collection of 3d urban scenes with rich details. The sheer amount of data brings a lot of opportunities but also poses tremendous challenges for both academic research and industrial applications on point cloud classification and building reconstruction. In this paper, we present an online algorithm to automatically detect and segment buildings from large scale unorganized 3d point clouds of urban scenes acquired by ground-Based LidAR devices. The core idea is that buildings can be observed in a street view separated by empty spaces such as alleys. By progressively projecting 3d points onto views along the scanning path, buildings can be detected as large regions with dense points. Experiments on several large scale datasets show that our approach can efficiently produce satisfactory results.

关键词： Three-dimensional displays Cameras Laser radar Tiles Sensors Rendering (computer graphics)

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Learning Part-Based Models for Animation from Surface Motion Capture

Learning Part-Based Models for Animation from Surface Motion...

引用

international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Margara Tejera Adrian Hilton Centre for Vision Speech and Signal Processing University of Surrey Guildford UK

Surface motion capture (Surf Cap) enables 3d reconstruction of human performance with detailed cloth and hair deformation. However, there is a lack of tools that allow flexible editing of Surf Cap sequences. In this paper, we present a Laplacian editing technique that constrains the mesh deformation to plausible surface shapes learnt from a set of examples. A part-Based representation of the mesh enables learning of surface deformation locally in the space of Laplacian coordinates, avoiding correlations between body parts while preserving surface details. This extends the range of animation with natural surface deformation beyond the whole-body poses present in the Surf Cap data. We illustrate successful use of our tool on three different characters.

关键词： Laplace equations Animation Shape deformable models Vectors Correlation Interpolation

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Accurate Georegistration of Point Clouds Using Geographic data

Accurate Georegistration of Point Clouds Using Geographic Da...

引用

international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Chun-Po Wang Kyle Wilson Noah Snavely Cornell University USA

The Internet contains a wealth of rich geographic information about our world, including 3d models, street maps, and many other data sources. This information is potentially useful for computer vision applications, such as scene understanding for outdoor Internet photos. However, leveraging this data for vision applications requires precisely aligning input photographs, taken from the wild, within a geographic coordinate frame, by estimating the position, orientation, and focal length. To address this problem, we propose a system for aligning 3d structure-from-motion point clouds, produced from Internet imagery, to existing geographic information sources, including Google Street View photos and Google Earth 3d models. We show that our method can produce accurate alignments between these data sources, resulting in the ability to accurately project geographic data into images gathered from the Internet, by ``Googling'' a depth map for an image using sources such as Google Earth.

关键词： Three-dimensional displays Solid modeling Computational modeling Cameras Google Buildings Earth

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3d Object Recognition by Surface Registration of Interest Segments

3D Object Recognition by Surface Registration of Interest Se...

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international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Joseph Lam Michael Greenspan Department Electrical & Computer Engineering Queen's University Kingston Canada Department Electrical & Computer Engineering School of Computing Queen's University Kingston Canada

An object recognition system Based on registering repeatable interest segments from 3d surfaces is presented. The strength of this approach lies in its independence of local features, which can be unreliable when corrupted by noise, and indistinct for certain objects and surfaces. The proposed framework is Based on recent advances in segmenting 3d data into repeatable interest segments, followed by efficient surface registration of model and scene segments, where pose clustering returns the best pose candidates. A quality measure Based on reprojection of the model points and pose refinement are then used to select the best pose. The proposed method is demonstrated experimentally to be both accurate and robust when tested against a variety of partially occluded free-form objects in cluttered scenes, achieving an average accuracy of 93% on an accurate and high resolution LidAR data set, and 81% on a noisy and low resolution Kinect data set.

关键词： Three-dimensional displays Feature extraction Object recognition Sensors Laser radar Computational modeling Robustness

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deriving Motion Constraints in Finger Joints of Individualized Hand Model for Manipulation by data Glove

Deriving Motion Constraints in Finger Joints of Individualiz...

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international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Takuya Funatomi Takuya Yamane Hirotane Ouchida Masaaki Iiyama Michihiko Minoh Kyoto University Kyoto Japan

In this paper, we propose a novel method of skeleton estimation for the purpose of constructing and manipulating individualized hand models via a data glove. To reconstruct actual hand accurately, we derive motion constraints in fully 6-dOF at the joints without assuming either a center of rotation or a joint axis. The constraints are derived by regression analysis on the configuration of the finger segments with respect to the sensor data. In order to acquire pairs of the configuration and the sensor data, we introduce graspable reference objects for reproducing postures with and without the data glove. To achieve accurate regression on fewer samples, we introduce a regression model according to a detailed investigation using a fused motion capture system, which enabled us to perform optical motion capture and sensor data collection simultaneously. The effectiveness of the method is demonstrated through practical applications involving grasped reference objects.

关键词： Joints Motion segmentation data models data gloves Shape Regression analysis Image reconstruction

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Watertight Planar Surface Meshing of Indoor Point-Clouds with Voxel Carving

Watertight Planar Surface Meshing of Indoor Point-Clouds wit...

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international Conference on 3d Imaging, Modeling, processing, visualization and transmission (3dIMPVT)

作者： Eric Turner Avideh Zakhor Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA USA

3d modeling of building architecture from point-cloud scans is a rapidly advancing field. These models are used in augmented reality, navigation, and energy simulation applications. State-of-the-art scanning produces accurate point-clouds of building interiors containing hundreds of millions of points. Current surface reconstruction techniques either do not preserve sharp features common in a man-made structures, do not guarantee water tightness, or are not constructed in a scalable manner. This paper presents an approach that generates watertight triangulated surfaces from input point-clouds, preserving the sharp features common in buildings. The input point-cloud is converted into a voxelized representation, utilizing a memory-efficient data structure. The triangulation is produced by analyzing planar regions within the model. These regions are represented with an efficient number of elements, while still preserving triangle quality. This approach can be applied to data of arbitrary size to result in detailed models. We apply this technique to several data sets of building interiors and analyze the accuracy of the resulting surfaces with respect to the input point-clouds.

关键词： Buildings Computational modeling Surface reconstruction data structures Memory management Geometry Ray tracing

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