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

作者： Limin Shang Michael Greenspan Department of Electrical & Computer Engineering Queen's University Kingston ONT Canada School of Computing Queen's University Kingston ONT Canada

A novel algorithm is introduced to estimate the pose of objects from sparse range data. Pose determination is tackled by employing the ICP algorithm to find corresponding local minima between a preprocessed model and the runtime data. Unlike other existing algorithms that try to avoid local minima, here local minima are used as effective feature vectors for generating multiple hypotheses of the pose. These hypotheses are then examined and verified using the bounded Hough transform, which is more robust than using the registration error directly. Only a small number of iterations (e.g., 5) is needed for each ICP at both preprocessing and runtime, which makes the technique efficient. The algorithm has been implemented and tested on a variety of objects, including freeform models, using both simulated and real data from Lidar and stereovision sensors. The experimental results show the technique to be both effective and efficient, executing at multiple frames per second on standard hardware. In addition, it functions well with very sparse data, possibly comprising only hundreds of points per frame, and it is also robust to measurement error and outliers.

关键词： Robustness Iterative closest point algorithm Runtime Embedded computing Impedance matching Tracking State-space methods Potential well data engineering Testing

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Johnson noise thermometry near the zinc freezing point using resistance-based scaling

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international JOURNAL OF THERMOPHYSICS 2007年第2期28卷 629-645页

作者： Tew, W. L. Labenski, J. R. Nam, S. W. Benz, S. P. dresselhaus, P. d. Burroughs, C. J. NIST Proc Measurement Div Gaithersburg MD 20899 USA Natl Inst Stand & Technol Div Optoelect Boulder CO 80303 USA Natl Inst Stand & Technol Quantum Elect Metrol Div Boulder CO 80303 USA

Johnson noise thermometry (JNT) is a primary method of measuring temperature which can be applied over wide ranges. The National Institute of Standards and Technology (NIST) is currently using JNT to determine the deviations of the international Temperature Scale of 1990 (ITS-90) from the thermodynamic temperature in the range of 505-933 K, overlapping the ranges of both acoustic gas-based and radiation-based thermometry. Advances in digital electronics have now made viable the computationally intensive and data-volume-intensive processing required for JNT using noise-voltage correlation in the frequency domain. The spectral noise power, and consequently the thermodynamic temperature T, of a high-temperature JNT probe is determined relative to a known reference spectrum using a switched-input digital noise-voltage correlator and simple resistance-scaling relationships. Comparison of the JNT results with standard platinum resistance thermometers calibrated on the ITS-90 gives the deviation of the thermodynamic temperature from the temperature on the ITS-90, T - T-90. Statistical uncertainties under 50 mu K center dot K-1 are achievable in less than 1 day of integration by fitting the effects of transmission-line time constants over bandwidths of 450 kHz. The methods and results in a 3 K interval near the zinc freezing point (T (90-ZnFP) equivalent to 692.677 K) are described. Preliminary results show agreement between the JNT-derived temperatures and the ITS-90.

关键词： ITS-90 Johnson noise noise thermometry temperature

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A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning

A Cross Branch Fusion-Based Contrastive Learning Framework f...

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

作者： Chengzhi Wu Qianliang Huang Kun Jin Julius Pfrommer Jürgen Beyerer Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Germany Department of Automation Tsinghua University China System Technologies and Image Exploitation IOSB Fraunhofer Institute of Optronics Germany

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

Contrastive learning is an essential method in self-supervised learning. It primarily employs a multi-branch strategy to compare latent representations obtained from different branches and train the encoder. In the case of multi-modal input, diverse modalities of the same object are fed into distinct branches. When using single-modal data, the same input undergoes various augmentations before being fed into different branches. However, all existing contrastive learning frameworks have so far only performed contrastive operations on the learned features at the final loss end, with no information exchange between different branches prior to this stage. In this paper, for point cloud unsupervised learning without the use of extra training data, we propose a Contrastive Cross-branch Attention-based framework for Point cloud data (termed PoCCA), to learn rich $3 d$ point cloud representations. By introducing sub-branches, PoCCA allows information exchange between different branches before the loss end. Experimental results demonstrate that in the case of using no extra training data, the representations learned with our self-supervised model achieve state-of-the-art performances when used for downstream tasks on point clouds.

关键词： Point cloud compression Representation learning Three-dimensional displays Training data Benchmark testing data models Task analysis

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HOC-Search: Efficient CAd Model and Pose Retrieval From RGB-d Scans

HOC-Search: Efficient CAD Model and Pose Retrieval From RGB-...

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

作者： Stefan Ainetter Sinisa Stekovic Friedrich Fraundorfer Vincent Lepetit Institute for Computer Graphics and Vision Graz University of Technology Graz Austria LIGM École des Ponts Univ Gustave Eiffel CNRS Marne-la-Vallée France

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

We present an automated and efficient approach for retrieving high-quality CAd models of objects and their poses in a scene captured by a moving RGB-d camera. We first investigate various objective functions to measure similarity between a candidate CAd object model and the available data, and the best objective function appears to be a ”render-and-compare” method comparing depth and mask rendering. We thus introduce a fast-search method that approximates an exhaustive search based on this objective function for simultaneously retrieving the object category, a CAd model, and the pose of an object given an approximate 3d bounding box. This method involves a search tree that organizes the CAd models and object properties including object category and pose for fast retrieval and an algorithm inspired by Monte Carlo Tree Search, that efficiently searches this tree. We show that this method retrieves CAd models that fit the real objects very well, with a speed-up factor of 10$\times$ to 120$\times$ compared to exhaustive search. We used our method to automatically retrieve CAd models for objects in the ScanNet dataset; our annotations are available at https://***/stefanainetter/SCANnotatedataset.

关键词： Training Point cloud compression Solid modeling Three-dimensional displays Monte Carlo methods Object detection Search problems

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Real-Time Human Posture Reconstruction in Wireless Smart Camera Networks

Real-Time Human Posture Reconstruction in Wireless Smart Cam...

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international symposium on Information processing in Sensor Networks (IPSN)

作者： Chen Wu Hamid Aghajan Richard Kleihorst Wireless Sensor Networks Laboratory University of Stanford USA NXP Semiconductors Research Eindhoven Netherlands

ISBN: (纸本)9780769531571

While providing a variety of intriguing application opportunities, a vision sensor network poses three key challenges. High computation capacity is required for early vision functions to enable real-time performance. Wireless links limit image transmission in the network due to both bandwidth and energy concerns. Last but not least, there is a lack of established vision-based fusion mechanisms when a network of cameras is available. In this paper a distributed vision processing implementation of human pose interpretation on a wireless smart camera network is presented. The motivation for employing distributed processing is to both achieve real-time vision and provide scalability for developing more complex vision algorithms. The distributed processing operation includes two levels. One is that each smart camera processes its local vision data, achieving spatial parallelism. The other is that different functionalities of the whole line of vision processing are assigned to early vision and object-level processors, achieving functional parallelism based on the processor capabilities. Aiming for low power consumption and high image processing performance, the wireless smart camera is based on an SIMd (single-instruction multiple-data) video analysis processor, an 8051 micro-controller as the local host, and wireless communication through the IEEE 802.15.4 standard. The vision algorithm implements 3d human pose reconstruction. From the live image data from the sensor the smart camera acquires critical joints of the subject in the scene through local processing. The results obtained by multiple smart cameras are then transmitted through the wireless channel to a central PC where the 3d pose is recovered and demonstrated in a virtual reality gaming application. The system operates in real time with a 30 frames/sec rate.

关键词： Humans Smart cameras Wireless sensor networks Image reconstruction Intelligent sensors distributed processing Parallel processing Computer vision High performance computing Image communication

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data analisis of 4d phase contrast MRI in healthy and non-healthy patients

Data analisis of 4D phase contrast MRI in healthy and non-he...

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international symposium on Image and Signal processing and Analysis

作者： Eduardo Soudah Maurizio Bordone Marcelino Rodriguez Jorge S. Pérez Chi-Hion Li Francesc Carreras UPC International Center for Numerical Methods in Engeneering (CIMNE) Spain Clinical and Translational Cardiology Sant Pau Biomedical Research Institute Spain

Time-resolved, 3-dimensional phase-contrast magnetic resonance imaging (3d+t PCMRI) is employed to obtain complete spatial and temporal coverage of the vessels blood combined with spatially registered 3-directional pulsatile blood flow velocities[1][2]. Recent studies have reported that Wall Shear Stress (WSS) quantification from PCMRI are able to use the WSS as biomarkers for different aortas pathologies [3]. Figure [1] shows the pathline visualization of blood flow during one cardiac cycle in the heart of a healthy patient at peak early LV filling, diastasis, peak atrial contraction, and peak systole.

关键词： Blood flow Three-dimensional displays Biomedical imaging Magnetic resonance Magnetic resonance imaging Stress Pathology

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Performance Improvement for OFdM-RoF Transported 60 GHz System using Spatial diversity and Multiplexing

Performance Improvement for OFDM-RoF Transported 60 GHz Syst...

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IEEE international Conference on Communications (ICC) / Wireless Communications symposium / 3rd Workshop on Optical Wireless Communications (OWC)

作者： Habib, Usman Aighobahi, Anthony E. Nair, Manish Zhu, Huiling Quinlan, Terence Walker, Stuart d. Gomes, Nathan J. Univ Kent Commun Res Grp Canterbury Kent England Univ Essex Sch Comp Sci & Elect Engn Colchester Essex England

ISBN: (纸本)9781509015252

60 GHz system architectures with Radio over Fiber (RoF) transport and integrated transmitters/receivers provide a comprehensive solution for future mobile systems. Since 60 GHz communication relies on line-of-sight (LoS) conditions and narrow-beam antennas to compensate the high path-loss, it has limitations in terms of coverage for multiple user locations. In this paper, performance analysis of a 60 GHz integrated transmitter and receiver system supported by RoF transport has been performed experimentally at different user locations for up to 1.5m transmission distance. Extension of experimental results to prove feasibility for longer distances has been shown with a simulation model, whose results at various shorter distances have been benchmarked against the acquired experimental results at different user locations. A modified version of the Saleh Valenzuela channel has been used to model the millimeter wave (mmW) LoS indoor experimental environment. Furthermore, as a proof of concept, we present an experimental analysis demonstrating an improvement in performance of the proposed RoF based 60 GHz system using spatial diversity and multiplexing. Channel measurements at different transmitter/receiver locations and their processing have shown that an improvement (decrease from 12.5% to 10.5%) in Error Vector Magnitude (EVM) can be achieved using the Alamouti Space Time Block Coding algorithm. Then it has been shown that a two-fold data rate increase can be obtained by combining data from two transmitter locations using the Zero Forcing algorithm.

关键词： Radio over Fiber Remote Antenna Unit Space Time Block Coding Zero Forcing Error Vector Magnitude

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Performance Study of SIMd Programming Models on Intel Multicore Processors

Performance Study of SIMD Programming Models on Intel Multic...

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IEEE international symposium on Parallel and distributed processing Workshops and Phd Forum (IPdPSW)

作者： Peter Kristof Hongtao Yu Zhiyuan Li Xinmin Tian Department of Computer Science Purdue University West Lafayette IN USA Mobile Computing and Compilers SSG Intel Corporation Santa Clara CA USA

ISBN: (纸本)9781467309745

Modern multicore hardware employs a variety of parallel execution units, including multiple CPU cores for executing multiple threads simultaneously, vector units such as the Intel SIMd on the CPU cores, as well as GPU-like processing arrays. Availability of such unprecedented level of parallelism on main-stream computers offers an enormous potential to enable a new generation of computation-intensive nontraditional applications. On the other hand, how to best harness the hardware parallelism presents a new challenge to application programmers, language designers and compiler developers. In this paper, we evaluate the impact of several different parallel execution models, especially the new SIMd vectorization methods, supported by the latest Intel ICC compiler (version 12.1), using three computation-intensive nontraditional parallel applications as the test workload. Unlike traditional numerical programs, these applications use highly irregular data structures and therefore present nontrivial challenges to effective use of SIMd vector units. The first application is a game engine architecture requiring real-time performance. The second application involves a kd-tree traversal, which is typical to the state-of-the-art 3d ray-tracing applications. The last application processes data for large-scale weather visualization system in the order of tens of minutes. We compare the execution time of these codes using different SIMd models supported by ICC in conjunction with parallel threading under TBB and OpenMP.

关键词： Vectors Games Program processors Parallel processing Engines Benchmark testing Computational modeling

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MIMO measurements of communication signals and application of blind source separation

MIMO measurements of communication signals and application o...

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IEEE international symposium on Signal processing and Information Technology (ISSPIT)

作者： J. Rinas K.d. Kammeyer Department of Communications Engineering Universität Bremen Germany

In this paper we present a flexible multiple input multiple output (MIMO) measurement system for communication signals in the 2.4 GHz band. We present some measurements of the digital to digital transmission channel which includes all impairments of the hardware realization. Using this system we perform a multi-layer transmission of communication signals. At the receiver side we use blind source separation (BSS) techniques as front-end processing to avoid estimation and synchronization problems. In order to improve the estimation of the channel and the symbol detection, we propose an iterative approach, which uses the knowledge of the finite symbol alphabet but does not need additional training data.

关键词： MIMO Blind source separation Transmitters Source separation detection algorithms Signal to noise ratio Signal processing Frequency Time measurement Hardware

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Restoration of Motion Blur in Time-of-Flight depth Image Using data Alignment

Restoration of Motion Blur in Time-of-Flight Depth Image Usi...

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

作者： Zhuo Chen Peilin Liu Fei Wen Jun Wang Rendong Ying Shanghai Jiao Tong University

ISBN: (数字)9781728181288

ISBN: (纸本)9781728181295

Time-of-flight (ToF) sensors are vulnerable to motion blur in the presence of moving objects. This is due to the principle of ToF camera that it estimates depth from the phase-shift between emitted and received modulated signals. And the phase-shift is measured by four sequential phase-shifted images, which is assumed to be consistent in an integration time. However, object motion would give rise to disparity among the four phase-shifted images, contributing to unreliable depth measurement. In this paper, we propose a novel method that is capable of aligning the four phase-shifted images through investigating the electronic value of each pixel in the phase images. It consists of two steps, motion detecting and deblurring. Furthermore, a refinement utilizing an additional group of phase-shifted images is adopted to further improve the accuracy of depth measurement. Experiment results on a new elaborated dataset with ground-truth demonstrate that the proposed method compares favorably over existing methods in both accuracy and runtime. Particularly, the new method can achieve the best accuracy while being computationally efficient that can support real-time running.

关键词： Cameras Phase measurement Image restoration Sensors Optical imaging Adaptive optics Three-dimensional displays

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