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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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Approximate k-d tree search for efficient ICP

Approximate k-d tree search for efficient ICP

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

作者： M. Greenspan M. Yurick School of Computing Queen's University Kingston ONT Canada

A method is presented that uses an approximate nearest neighbor method for determining correspondences within the iterative closest point algorithm. The method is based upon the k-d tree. The standard k-d tree uses a tentative backtracking search to identify nearest neighbors. In contrast, the approximate k-d tree (Ak-d tree) applies a depth-first nontentative search to the k-d tree structure. This search improves runtime efficiency, with the tradeoff of reducing the accuracy of the determined correspondences. This approximate search is applied to early iterations of the iterative closest point algorithm, transitioning to the standard k-d tree for the final iterations after the change in the mean square error of the correspondences becomes sufficiently small. The method benefits both from the improved time performance of the approximate search in early iterations as well as the full accuracy of the complete search in later iterations. Experimental results indicate that the time efficiency of Ak-d tree is superior to the k-d tree and Elias for moderately large point sets. The change in the shape of the minimum potential well space is subtle, and the convergence properties are often identical. In those cases where the global minimum was not achieved, the difference in final mse was very small. In one trial, Ak-d tree converged faster to a better minimum with a smaller mse, which indicates that the use of approximate methods may be beneficial in the presence of outliers.

关键词： Iterative closest point algorithm Nearest neighbor searches Runtime Neural networks Tree data structures Mean square error methods Shape Potential well Convergence Image converters

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Learning to Estimate 6doF Pose from Limited data: A Few-Shot, Generalizable Approach using RGB Images

Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot...

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

作者： Panwang Pan Zhiwen Fan Brandon Y. Feng Peihao Wang Chenxin Li Zhangyang Wang ByteDance University of Texas at Austin MIT The Chinese University of Hong Kong

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

The accurate estimation of six degrees-of-freedom (6doF) object poses is essential for many applications in robotics and augmented reality. However, existing methods for 6doF pose estimation often depend on CAd templates or dense support views, restricting their usefulness in real-world situations. In this study, we present a new cascade framework named Cas6d for few-shot 6doF pose estimation that is generalizable and uses only RGB images. To address the false positives of target object detection in the extreme few-shot setting, our framework utilizes a self-supervised pre-trained ViT to learn robust feature representations. Then, we initialize the nearest top-K pose candidates based on similarity score and refine the initial poses using feature pyramids to formulate and update the cascade warped feature volume, which encodes context at increasingly finer scales. By discretizing the pose search range using multiple pose bins and progressively narrowing the pose search range in each stage using predictions from the previous stage, Cas6d can overcome the large gap between pose candidates and ground truth poses, which is a common failure mode in sparse-view scenarios. Experimental results on the LINEMOd and GenMOP datasets demonstrate that Cas6d outperforms state-of-the-art methods by 9.2% and 3.8& accuracy (Proj-5) under the 32-shot setting compared to OnePose++ and Gen6d. Our framework also performs best under the full-shot setting with all support views. Code is avilable at https://***/***/paulpanwang/Cas6d.

关键词： Three-dimensional displays Codes Pose estimation Object detection Feature extraction Robots Augmented reality

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The Visible Cell™ Project: Changing the Way We Think about Cells

The Visible Cell™ Project: Changing the Way We Think about ...

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international symposium on Parallel Architectures, Algorithms and Networks (ISPAN)

作者： Mark Ragan Brad Marsh The Visible Cell™ project team Beta Cell Structural Biology/Cellular Tomography research University of Queensland

Constructing a realistic systems biology of the mammalian cell will require us to describe molecular and cellular "parts", and to model and simulate their relationships in space and time. To date, most modelling and simulation has focused on temporally dynamic processes including pathways of gene regulation, metabolism and cellular signalling. A goal of the Visible Celltrade project is to integrate spatial as well as temporal models within a common data, computational and visualisation environment to support hypothesis-generation and hypothesis-testing by biologists and modellers. A unique feature of this project is our use of actual 3-d cellular structure data, reconstructed from medium-resolution confocal video microscopy and high-resolution electron tomography, to generate the matrix for our visualisation environment. Molecular sequence and protein structure data are obtained from distributed databases via web services. The Visible Celltrade has been designed as an e-research project and implements computational and data grid standards and technologies.

关键词： Biological system modeling Computational modeling data visualization Systems biology Cells (biology) Biochemistry Signal processing Biology computing Electron microscopy Tomography

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Characterization of local 3d rough surfaces using UWB near-range phase-based GPR signatures from wide-beamwidth antennas

Characterization of local 3D rough surfaces using UWB near-r...

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IEEE international symposium on Geoscience and Remote Sensing (IGARSS)

作者： B. Sai L.P. Ligthart International Research Centre for Telecommunications-transmission and Radar (IRCTR) Department of Electrical Engineering Faculty of Information Technology and Systems Delft University of Technnology Delft Netherlands

This paper pertains to further investigations on using an ultra wideband (UWB) multistatic coherent ground-penetrating radar (GPR) technique for precise profiling of the rough surfaces in three-dimensional space. The method is essentially based on the phase processing of the sliced layers of three-dimensional rough surfaces with multiple sub-frequency bands. The data acquired in the near range by a UWB stepped-frequency continuous-wave GPR with wide-beam antennas over a compound surface are used to verify the method. It was found that in the near-range measurements the range side-lobe interference effects and the reflections from the measurement surroundings sometimes have a significant influence on the target phase and amplitude responses, and consequently degrade the localization of the targets. The present study on this issue shows that within the ultra wideband, some sub-frequency bands are less sensitive to the measurement surroundings, but still sensitive to the target area. With the selected sub-frequency bands the image of the compound surface reconstructed in the surface height domain shows good agreement with the practical geometry of the rough surfaces.

关键词： Rough surfaces Surface roughness Ground penetrating radar Ultra wideband antennas Surface reconstruction Ultra wideband technology Antenna measurements Phase measurement Spaceborne radar Interference

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Protocol for streaming compressed 3-d animations over lossy channels

Protocol for streaming compressed 3-D animations over lossy ...

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IEEE international Conference on Multimedia and Expo (ICME)

作者： G. Al-Regib Y. Altunbasak J. Rossignac R. Mersereau Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA Graphics Visualization and Usability Center Georgia Institute of Technology Atlanta GA USA Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA

We propose a protocol for efficient streaming of 3-d animations over lossy channels. In order to improve the expected quality on the client's side, we first transmit a crude model of the 3-d mesh, of its texture, and of its immediate evolution. We endow this data with significant error-protection against transmission error. Then we transmit a series of upgrades that refine the accuracy of the model and/or of the animation. These are encoded with lower levels of error protection that is proportional to their impact on the quality of the upgraded animation. We propose the following types of upgrade chunks: selection of a subset of vertices, adjustments of the accuracy of the positions of the selected vertices, connectivity refinements, motion adjustments of the selected subset of vertices, adjustments of the accuracy of the texture coordinates of the selected vertices, and upgrade of the quality of the texture. Finally, given the allocated bit-budget, we determine the optimal number of both source and channel coding bits assigned for each chunk to maximize the animation quality on the client's side. The optimization takes into account both the bandwidth and the error characteristics of the channel.

关键词： Protocols Animation Internet Streaming media Bandwidth Layout Image coding visualization Electronic mail Protection

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Multi-View Remote Sensing Image Segmentation with Sam Priors

Multi-View Remote Sensing Image Segmentation with Sam Priors

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IEEE international symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zipeng Qi Chenyang Liu Zili Liu Hao Chen Yongchang Wu Zhengxia Zou Zhenwei Shi Image Processing Centre School of Astronautics Beihang University Beijing China Shanghai AI Lab Department of Guidance Navigation and Control School of Astronautics Beihang University Beijing China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Multi-view segmentation in Remote Sensing (RS) seeks to segment images from diverse perspectives within a scene. Recent methods leverage 3d information extracted from an Implicit Neural Field (INF), bolstering result consistency across multiple views while using limited accounts of labels (even within 3-5 labels) to streamline labor. Nonetheless, achieving superior performance within the constraints of limited-view labels remains challenging due to inadequate scene-wide supervision and insufficient semantic features within the INF. To address these. we propose to inject the prior of the visual foundation model-Segment Anything(SAM), to the INF to obtain better results under the limited number of training data. Specifically, we contrast SAM features between testing and training views to derive pseudo labels for each testing view, augmenting scene-wide labeling information. Subsequently, we introduce SAM features via a transformer into the INF of the scene, supplementing the semantic information. The experimental results demonstrate that our method outperforms the mainstream method, confirming the efficacy of SAM as a supplement to the INF for this task.

关键词： Training Image segmentation visualization Three-dimensional displays Semantics Training data Transformers

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A collaborative simulation-analysis workflow for computational neuroscience Using HPC 1

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1st JARA-HPC symposium on High-Performance Scientific Computing, JHPCS 2016

作者： Senk, Johanna Yegenoglu, Alper Amblet, Olivier Brukau, Yury davison, Andrew Lester, david Roland Lührs, Anna Quaglio, Pietro Rostami, Vahid Rowley, Andrew Schuller, Bernd Stokes, Alan Barry Van Albada, Sacha Jennifer Zielasko, daniel diesmann, Markus Weyers, Benjamin denker, Michael Grün, Sonja JARA-BRAIN Institute I Forschungszentrum Jülich Jülich Germany École Polytechnique Fédérale de Lausanne Geneva Switzerland Centre National de la Recherche Scientifique Gif-sur-Yvette France Department of Computer Science University of Manchester Manchester United Kingdom Forschungszentrum Jülich Jülich Germany Visual Computing Institute RWTH Aachen University Aachen Germany JARA-HPC Aachen Germany Department of Psychiatry Psychotherapy and Psychosomatics Medical Faculty RWTH Aachen University Aachen Germany Department of Physics Faculty 1 RWTH Aachen University Aachen Germany Theoretical Systems Neurobiology RWTH Aachen University Aachen Germany

ISBN: (数字)9783319538624

ISBN: (纸本)9783319538617

Workflows for the acquisition and analysis of data in the natural sciences exhibit a growing degree of complexity and heterogeneity, are increasingly performed in large collaborative efforts, and often require the use of high-performance computing (HPC). Here, we explore the reasons for these new challenges and demands and discuss their impact with a focus on the scientific domain of computational neuroscience. We argue for the need of software platforms integrating HPC systems that allow scientists to construct, comprehend and execute workflows composed of diverse data generation and processing steps using different tools. As a use case we present a concrete implementation of such a complex workflow, covering diverse topics such as HPC-based simulation using the NEST software, access to the SpiNNaker neuromorphic hardware platform, complex data analysis using the Elephant library, and interactive visualization methods for facilitating further analysis. Tools are embedded into a web-based software platform under development by the Human Brain Project, called the Collaboratory. On the basis of this implementation, we discuss the state of the art and future challenges in constructing large, collaborative workflows with access to HPC resources. © Springer international Publishing AG 2017.

关键词： visualization

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Low Cost LidAR Prototype design for 3d Mapping

Low Cost LiDAR Prototype Design for 3D Mapping

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international Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Yanto Budisusanto Mokhamad Nur Cahyadi Imam Wahyudi Farid Muchammad Rizki Ubaidillah daud Wahyu Imani Departement of Geomatics Engineering Faculty of Civil Planning and Geo Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Electrical Automation Engineering Faculty of Vocational Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9781665499705

The general public started to recognize Light detection and Ranging when the astronauts used it for mapping the surface of the moon in early 1970s. The need for using LidAR Technology is for low-cost mapping surveys will make it easier for surveyors as well as research to obtain fairly accurate data at a more economical price. LidAR technology works based on the time of flight (ToF) principle, using the transmission time and laser light reception to calculate the distance between the tool and the reflected object. The LidAR device has a sensor that leads to its use which equipped by the motor as a driver so that it can rotate 360 degrees within a certain distance. LidAR is an expensive survey tool, with the price ranging around 6600 USd due to its quality in conducting detailed data result. Therefore, this study used the LidAR priced below 100 USd in order to minimize operational costs, which is TF mini LidAR. This sensor has a detection range of up to 40 m, has a viewing angle of 2.3°, and able to calculate distances with an accuracy of ± 2.5 cm. This study also used GPS to determine coordinate position from the results of LidAR processing. The advantage of LidAR is able to detect an object in the detected location [1]. The usage of LidAR sensor testing has been carried out in this study. The purpose of this experiment is to integrate Low Cost LidAR with Low Cost GPS to produce a product that able to perform Low Cost 3-dimensional mapping. This survey has been carried out in a room sized 4x3 m. The data in the form of X, Y, and Z are then processed using open source software with sufficient results to describe 3d-visualization.

关键词： Laser radar Costs Three-dimensional displays Moon Prototypes distance measurement Laser beams

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Multi-GPU based near real-time preprocessing and releasing system of optical satellite images

Multi-GPU based near real-time preprocessing and releasing s...

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IEEE international symposium on Geoscience and Remote Sensing (IGARSS)

作者： Liuyang Fang Mi Wang Hexiang Ying Fen Hu Mapping and Remote Sensing Wuhan University Hubei China Geomatics Center of Zhejiang Province Hangzhou Zhejiang China National Administration of Surveying Satellite Surveying and Mapping Application Center (SASMAC) Beijing China

The volume of the image data collected by optical satellites is increasing tremendously nowadays. In this paper, we present our recent research on the multi-graphics processing unit (multi-GPU) based near real-time preprocessing and releasing system (RPRS) of optical satellite images. RPRS consists of two sub-systems, namely, the image preprocessing sub-system and the image releasing sub-system. The image preprocessing sub-system ports the four image processors (i.e. relative radiometric correction, median filtering, modulation transfer function compensation and geometric correction) to the GPUs for execution with the compute unified device architecture (CUdA). Both the basic GPU implementation and three optimization measures are presented. To validate our strategy, an entire ZY-3 nadir image strip consisting of 80 images is used for experiment on the multi-GPU system that consists of four NVIdIA Tesla M2050 GPUs. The results show that the efficiency of the processors is substantially accelerated by the use of GPU. The speedup ratios are between 10.94 and 44.89. Moreover, when using all the four GPUs, the processing of the entire image strip only costs 19 min 45 s, which could meet the near realtime preprocessing requirement. The image releasing system affords the direct visualization of the georeferenced images on the geographic base map of GeoGlobe, a Google Earth like 3d spatial information releasing platform developed by State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, China. It is very convenient for the follow-up relevant applications.

关键词： Graphics processing units Satellites Satellite broadcasting Remote sensing Adaptive optics Optical filters

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Post-disaster damage assessment through coherent change detection on SAR imagery

Post-disaster damage assessment through coherent change dete...

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2018 ISPRS TC III Mid-Term symposium on developments, Technologies and Applications in Remote Sensing

作者： Guida, L. Boccardo, P. donevski, I. Lo Schiavo, L. Molinari, M.E. Monti-Guarnieri, A. Oxoli, d. Brovelli, M.A. Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy Interuniversity Department of Regional and Urban Studies and Planning Politecnico di Torino Turin Italy Department of Electronics and Telecommunications Politecnico di Torino Turin Italy Department Of Civil And Environmental Engineering Politecnico di Milano Milan Italy

damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change detection (CCd) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings. © Authors 2018.

关键词： Synthetic aperture radar

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