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Measurement of 3-D strain distribution by means of high-resolution X-ray CT image and tracking of microstructural features

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JOURNAL OF THE JAPAN INSTITUTE OF METALS 2007年第2期71卷 181-186页

作者： Kobayashi, Masakazu Toda, Hiroyuki Kawai, Yuji Kobayashi, Toshiro Uesugi, Kentaro Wilkinson, David S. Maire, Eric Aoki, Yoshimitsu Toyohashi Univ Technol Dept Prod Syst Engn Toyohashi Aichi 4418580 Japan McMaster Univ Dept Mat Sci & Engn Hamilton ON L8S 4L8 Canada Inst Natl Sci Appl F-69621 Villeurbanne France Shibaura Inst Technol Dept Informat Engn Tokyo 1358548 Japan

Measurement of interior strain distribution has been developed based on the synchrotron radiation computed tomography (SR-CT). In metal deformation, local strain distribution differs from macroscopic strain due to microstructural factors such as grains, grain boundaries, particles, pores, voids, and cracks. A model sample, which was made from a copper alloy strengthened with alumina, was prepared containing artificial pores. Tensile loading was applied to the sample step by step. High-resolution tomographic experiment was performed at the third-generation synchrotron radiation facility (SPring-8) in Japan. Gravity center position, volume and surface area in the pores, which were regarded as markers in a tracking procedure, were measured by 3-D digital image analysis in the SR-CT images. The markers before and after the deformation were provided for registration and macroscopic strain correction before the tracking procedure. The marker tracking was carried out by means of matching parameter that was described as functions of distance, volume and surface at markers. The ratio of success tracking was evaluated in order to clarify whether the tracking method developed in this study was reliable. The 3-D strain distribution was represented successfully by the tracking results. A combination of high-resolution SR-CT and tracking of microstructural features is effective to visualize interior strain distribution in materials in 3-D.

关键词： tracking algorithm interior strain local strain synchrotron radiation computer tomography three-dimensional observation three-dimensional image analysis

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tracking the Warhead Among Objects Separation from the Reentry Vehicle in a Clear Environment

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DEFENCE SCIENCE JOURNAL 2009年第2期59卷 113-125页

作者： Liu, Cheng-Yu Chen, Chi-Teh Lee Ming Inst Technol Dept Elect Engn Taipei Taiwan

Separating a reentry vehicle into warhead, main body, and debris is a conventional and efficient means of producing a huge decoy and increasing the kinetic energy of the warhead. This procedure Causes the radar to track the main body and debris, which radar cross section are large. and ignore the warhead, is the most important part of the reentry vehicle. The warhead is difficult to identify after separation using standard tracking criteria. This study presents a novel tracking algorithm by integrating input estimation and modified probabilistic data association filter to identity warhead among objects separation from the reentry vehicle in a clear environment. The proposed algorithm provides a good tracking capability tor the warhead ignoring the radar cross sec(ion. Simulation results reveal that the errors between the Updated and warhead trajectorics are reduced to a small interval in a short time. Therefore, the radar can generate it beam to illuminate the right area and keep tracking the warhead all the time. This algorithm is Worthy of further Study and application.

关键词： Input estimation probabilistic data assocition filter extended Kalman filter tracking algorithm trajectory estimation

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Visual tracking using locality-constrained linear coding under a particle filtering framework

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IET COMPUTER VISION 2018年第2期12卷 196-207页

作者： Ding, Meng Wei, Li Cao, Yunfeng Wang, Jie Cao, Li Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat 29 Jiangjun St Nanjing Jiangsu Peoples R China Sci & Technol Electroopt Control Lab 25 Kaixuan St Luoyang Peoples R China Nanjing Univ Aeronaut & Astronaut Jin Cheng Coll 88 Hangjin St Nanjing Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Astronaut 29 Yudao St Nanjing Jiangsu Peoples R China

Visual target tracking has long been a challenging problem because of the variable appearance of the target with changing spatiotemporal factors. Therefore, it is important to design an effective and efficient appearance model for tracking tasks. This study proposes a tracking algorithm based on locality-constrained linear coding (LLC) under a particle filtering framework. A local feature descriptor is presented that can evenly represent the local information of each patch in the tracking region. LLC uses the locality constraints to project each local feature descriptor into its local-coordinate system. Compared with sparse coding, LLC can be performed very quickly for appearance modelling because it has an analytical solution derived by a three-step matrix calculation, and the computational complexity of the proposed tracking algorithm is o(eta x m x n). Both quantitative and qualitative experimental results demonstrate that the authors' proposed algorithm performs favourably against the 10 state-of-the-art trackers on 12 challenging test sequences. However, related experimental results show that the performance of their tracker is not effective enough for small tracking targets owing to a lack of sufficient local region information.

关键词： linear codes particle filtering (numerical methods) target tracking local region information computational complexity matrix calculation local feature descriptor LLC tracking algorithm spatiotemporal factors variable appearance visual target tracking particle filtering framework locality constrained linear coding visual tracking

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Computational tracking of Shear-Mediated Platelet Interactions with von Willebrand Factor

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CARDIOVASCULAR ENGINEERING AND TECHNOLOGY 2016年第4期7卷 389-405页

作者： Ralph, Adam Somers, Martin Cowman, Jonathan Voisin, Bruno Hogan, Emma Dunne, Hannah Dunne, Eimear Byrne, Barry Kent, Nigel Ricco, Antonio J. Kenny, Dermot Wong, Simon Natl Univ Ireland Irish Ctr High End Comp IT BldgUniv Rd Galway Ireland Dublin City Univ Biomed Diagnost Inst Dublin 9 Ireland Royal Coll Surgeons Ireland Biomed Diagnost Inst Dublin 2 Ireland Dublin Inst Technol Sch Mech & Design Engn Dublin 1 Ireland

The imaging of shear-mediated dynamic platelet behavior interacting with surface-immobilized von Willebrand factor (vWF) has tremendous potential in characterizing changes in platelet function for clinical diagnostics purposes. However, the imaging output, a series of images representing platelets adhering and rolling on the surface, poses unique, non-trivial challenges for software algorithms that reconstruct the positional trajectories of platelets. We report on an algorithm that tracks platelets using the output of such flow run experiments, taking into account common artifacts encountered by previously-published methods, and we derive seven key metrics of platelet dynamics that can be used to characterize platelet function. Extensive testing of our method using simulated platelet flow run data was carried out to validate our tracking method and derived metrics in capturing key platelet-vWF interaction-dynamics properties. Our results show that while the number of platelets present on the imaged area is the leading cause of errors, flow run data from two experiments using whole blood samples showed that our method and metrics can detect platelet property changes/differences that are concordant with the expected biological outcome, such as inhibiting key platelet receptors such as P2Y(1), glycoprotein (GP)Ib and GPIIb/IIIa. These findings support the use of our methodologies to characterize platelet function among a wide range of healthy and disease cohorts.

关键词： Platelet dynamics Whole blood flow-based assay Video fluorescence microscopy tracking algorithm

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Semantic and context features integration for robust object tracking

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IET IMAGE PROCESSING 2022年第5期16卷 1268-1279页

作者： Yao, Jinzhen Zhang, Jianlin Wang, Zhixing Shao, Linsong Chinese Acad Sci Key Lab Opt Engn Chengdu Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu 610200 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing Peoples R China

Siamese network-based object tracking learns features of a target object marked in the first frame and that of the object in subsequent frames simultaneously and then measures similarity between two features to recognize and locate the object. Owing to their efficiency and high accuracy, Siamese networks have attracted much attention recently. However, tracking accuracy decreases significantly when there are scale changes, occlusion, and pose variations due to the way that Siamese networks estimate feature similarity. To address this issue, the authors propose a tracking algorithm, named Semantic and context features integration for robust object tracking that integrates local and global features of the object. Local features provide context information for tracking parts of the object, while global features contain semantic information for tracking the object. The authors meticulously design local and global classification and regression heads and integrate them into one uniform framework to achieve integration tracking. This method effectively alleviates low accuracy in complex scenes such as scale changes, deformation, and occlusion. Numerous experiments demonstrate that this method achieves state-of-art (SOTA) performance with 45 FPS on a single RTX2060 Super GPU on public tracking datasets, including VOT2016, VOT2019, OTB100, GOT-10k, and LaSOT, and its effectiveness and efficiency is confirmed.

关键词： subsequent frames global classification regression analysis regression heads local features object tracking scale changes target object image representation learning (artificial intelligence) robust object tracking semantic information target tracking feature extraction global features Siamese network-based object tracking tracking accuracy tracking algorithm integration tracking Semantic context features integration context information object detection public tracking datasets feature similarity Siamese networks image classification

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tracking topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第16期77卷 20297-20324页

作者： Harakawa, Ryosuke Ogawa, Takahiro Haseyama, Miki Hokkaido Univ Grad Sch Informat Sci & Technol Sapporo Hokkaido Japan

A method to track topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery is presented in this paper. The proposed method enables users to understand the evolution of topics over time for discovering Web videos in which they are interested. A framework that enables extraction and tracking of the hierarchical structure, which contains Web video groups with various degrees of semantic broadness, is newly derived as follows: Based on network analysis using multimodal features, i.e., features of video contents and metadata, our method extracts the hierarchical structure and salient keywords that represent contents of each Web video group. Moreover, salient keyword matching, which is newly developed by considering salient keyword distribution, semantic broadness of each Web video group and initial topic relevance, is applied to each hierarchical structure obtained in different time stamps. Unlike methods in previous works, by considering the semantic broadness as well as the salient keyword distribution, our method can overcome the problem of the desired semantic broadness of topics being different depending on each user. Also, the initial topic relevance enables correction of the gap from an initial topic at the start of tracking. Consequently, it becomes feasible to track the evolution of topics over time for finding Web videos in which the users are interested. Experimental results for real-world datasets containing YouTube videos verify the effectiveness of the proposed method.

关键词： Web video Video retrieval Topic evolution tracking algorithm Network analysis

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Asynchronous Event-Based Visual Shape tracking for Stable Haptic Feedback in Microrobotics

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IEEE TRANSACTIONS ON ROBOTICS 2012年第5期28卷 1081-1089页

作者： Ni, Zhenjiang Bolopion, Aude Agnus, Joel Benosman, Ryad Regnier, Stephane Univ Paris 06 Inst Syst Intelligents & Robot F-75005 Paris France FEMTO ST Inst F-25000 Besancon France Univ Paris 06 Neuromorph Vis & Nat Computat Grp Vis Inst F-75005 Paris France

Micromanipulation systems have recently been receiving increased attention. Teleoperated or automated micromanipulation is a challenging task due to the need for high-frequency position or force feedback to guarantee stability. In addition, the integration of sensors within micromanipulation platforms is complex. Vision is a commonly used solution for sensing;unfortunately, the update rate of the frame-based acquisition process of current available cameras cannot ensure-at reasonable costs-stable automated or teleoperated control at the microscale level, where low inertia produces highly unreachable dynamic phenomena. This paper presents a novel vision-based microrobotic system combining both an asynchronous address event representation silicon retina and a conventional frame-based camera. Unlike frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events in a manner similar to the output cells of a biological retina, enabling high update rates. This paper introduces an event-based iterative closest point algorithm to track a microgripper's position at a frequency of 4 kHz. The temporal precision of the asynchronous silicon retina is used to provide a haptic feedback to assist users during manipulation tasks, whereas the frame-based camera is used to retrieve the position of the object that must be manipulated. This paper presents the results of an experiment on teleoperating a sphere of diameter around 50 mu m using a piezoelectric gripper in a pick-and-place task.

关键词： Dynamic vision sensor haptic feedback micromanipulation microrobotics tracking algorithm

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tracking structure suitable for L6 signal

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The Journal of China Universities of Posts and Telecommunications 2021年第4期28卷 64-74页

作者： Wang Yiting Ba Xiaohui Liu Xueyong Yang Ying Li Jian Chen Jie System on Chip Lab Institute of Microelectronics of the Chinese Academy of SciencesBeijing 100029China College of Electronic and Electrical Communication Engineering University of Chinese Academy of SciencesBeijing 100049China

A tracking structure suitable for L6 signal of quasi-zenith satellite system(QZSS) was proposed in order to track the L6 signal without other frequency assistance. Moreover, the tracking structure does not change the receiver’s hardware structure. The main difference between the proposed and the traditional tracking structure lies in the generation of local codes of E,P and L branches. The method of local code generation is designed in a two-stage manner. The first stage is the generation of the P branch local code with fast fouriertransform(FFT). In the second stage, the local codes of the E and L branches are obtained with the code-chip interval. The tracking structure can track and decode L6 signal separately, and track code shift keying(CSK)modulated signal as well. The structure was verified using both simulation data, generated in different conditions, and actual data obtained from QZSS satellites respectively. The results show that the improved tracking loop is able to track L6 signal without other frequency assitance. Furthermore, the biterror ratio(BER) of L6 tracking algorithm is lower than that of L1C/A assist L6 algorithm, when the Doppler remains a constant and reed solomn(RS)encode are applied. To be more specific, with the proposed structure the BER decreased by 11.40%, 17.07%, 15.00%, 11.15%, 5.19% when carrier to noise ratio(CNR) is 36-40 dB·Hz.

关键词： quasi-zenith satellite system L6 signal code shift keying modulation tracking algorithm

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GPU Parallel Computing algorithm in Target tracking of Space

GPU Parallel Computing Algorithm in Target Tracking of Space

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第四届智能结构与振动控制国际会议

作者： Tuo Ding The 8th Institute Shanghai Academy of Spaceflight Technology

Article careful analysis of existing processes and target tracking algorithm and part of the video image processing algorithm that consume large amount of data based *** algorithm for image pre-processing module and tracking module algorithm designed operational *** studies algorithm for image pre-processing module,and each was carried out in parallel GPU accelerated processing,and were tested in a unified CUDA computing *** data show that some parts of the algorithm can be improved after the adoption of CUDA target tracking algorithm optimized overall efficiency,has some practical significance.

关键词： GPU CUDA,Moving Target tracking algorithm

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Reliability verification-based convolutional neural networks for object tracking

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IET IMAGE PROCESSING 2019年第1期13卷 175-185页

作者： Hu, Xiaopeng Li, Jingting Yang, Yan Wang, Fan Dalian Univ Technol Sch Comp Sci & Technol 2 Linggong Rd Ganjingzi Dist Dalian Peoples R China Liaoning Normal Univ Sch Comp & Informat Technol 850 Huanghe Rd Shahekou Dist Dalian Peoples R China

The authors propose a tracking algorithm based on the reliability analysis of the convolutional neural network to avoid drift. In general, most tracking algorithms implemented with the deep network consist of a single network;they obtain the tracking results according to the confidence and perform updates with the samples, which are collected based on the previous target state. However, this kind of algorithm relies heavily on the accuracy of tracking results, and slight deviations can lead to improperly labelled training samples and degrade the network. Therefore, they design a verification network to guarantee the reliability of the tracking network by correcting the results and it can be connected to a tracking network by sharing convolutional layers. The reliability verification network estimates the accuracy of the results of the tracking network and discards ambiguous results to avoid accumulating errors. Specifically, the verification network can distinguish the target from the confused candidates more precisely because of the optimised training data. The training samples of the verification network consist of characteristics and labels, and they are optimised by feature selection and label enhancement, respectively. The experimental results illustrate the outstanding performance compared with several state-of-the-art methods on the challenging video sequences.

关键词： object tracking learning (artificial intelligence) feedforward neural nets reliability feature selection tracking network reliability verification-based convolutional neural networks object tracking tracking algorithm reliability analysis deep network single network improperly labelled training samples feature selection label enhancement convolutional layers

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