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2010 13th International Conference on Information Fusion最新文献

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On the observability of indirect filtering in vehicle tracking and localization using a fixed camera 基于固定摄像机的车辆跟踪定位中间接滤波的可观察性研究
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711901
L. Perera, P. Elinas
{"title":"On the observability of indirect filtering in vehicle tracking and localization using a fixed camera","authors":"L. Perera, P. Elinas","doi":"10.1109/ICIF.2010.5711901","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711901","url":null,"abstract":"In several vehicle tracking and localization applications, the initial position of a vehicle may be given by GPS measurements or other means. However, the information required for accurate tracking after initialization may only be available intermittently or not at all. In this paper, we demonstrate that the indirect or error form of state variables can be used in accurate bearing only tracking of a vehicle when the GPS measurements of its location are discontinued for some reason. Using Piece-wise Constant Systems Theory of Observability Analysis and the indirect form of the state variables for a constant velocity model we show that an object moving in a two-dimensional environment tracked by bearing only measurements using a fixed monocular camera is fully observable. We experimentally verify the theoretical results with simulations and real data from a fixed monocular camera tracking a pedestrian consistently when GPS measurements are discontinued.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130573019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive sensor data fusion in motion capture 运动捕捉中的自适应传感器数据融合
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711994
Shuyan Sun, X. Meng, Lianying Ji, Jiankang Wu, L. Wong
{"title":"Adaptive sensor data fusion in motion capture","authors":"Shuyan Sun, X. Meng, Lianying Ji, Jiankang Wu, L. Wong","doi":"10.1109/ICIF.2010.5711994","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711994","url":null,"abstract":"Micro-sensor human motion capture has shown its potentials because of its ubiquity and low cost. One of the biggest challenges in micro-sensor motion estimation is the drift problem caused by integration of angular rates to obtain orientation. To reduce the drift, existing algorithms make use of gravity and earth magnetic filed measured by accelerometers and magnetometers respectively. Unfortunately, body segment acceleration and environment magnetic disturbance produce strong interferences to the gravity and earth magnetic field measurement respectively. This paper presents a novel sensor fusion algorithm for drift-free orientation estimation, where a quaternion-based complementary Kalman filter is designed. To optimize the performance under interference, this filter fuses gyroscope, accelerometer and magnetometer signals adaptively based on their information confidence, which are evaluated by computing their interference level. The proposed algorithm showed least error compared with the existing methods in the quantitative experiments, and its effectiveness was also verified by the stable and accurate human motion estimation.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123856125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 34
Global robot localization with random finite set statistics 基于随机有限集统计量的机器人全局定位
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711873
A. Bishop, P. Jensfelt
{"title":"Global robot localization with random finite set statistics","authors":"A. Bishop, P. Jensfelt","doi":"10.1109/ICIF.2010.5711873","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711873","url":null,"abstract":"We re-examine the problem of global localization of a robot using a rigorous Bayesian framework based on the idea of random finite sets. Random sets allow us to naturally develop a complete model of the underlying problem accounting for the statistics of missed detections and of spurious/erroneously detected (potentially unmodeled) features along with the statistical models of robot hypothesis disappearance and appearance. In addition, no explicit data association is required which alleviates one of the more difficult sub-problems. Following the derivation of the Bayesian solution, we outline its first-order statistical moment approximation, the so called probability hypothesis density filter. We present a statistical estimation algorithm for the number of potential robot hypotheses consistent with the accumulated evidence and we show how such an estimate can be used to aid in re-localization of kidnapped robots. We discuss the advantages of the random set approach and examine a number of illustrative simulations.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123961029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
First-moment multi-object forward-backward smoothing 第一时刻多目标前后平滑
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711921
Daniel E. Clark
{"title":"First-moment multi-object forward-backward smoothing","authors":"Daniel E. Clark","doi":"10.1109/ICIF.2010.5711921","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711921","url":null,"abstract":"The optimal solution to the problem of detecting, tracking and identifying multiple targets can be found through a direct generalisation of the Bayes filter to multi-object systems using Mahler's Finite Set Statistics. Due to the inherent complexity of the multi-object Bayes filter, Mahler proposed to propagate the first-order multi-object moment density, known as the Probability Hypothesis Density (PHD), instead of the multi-object posterior. This was derived using the concept of the probability generating functional (p.g.fl.) from point process theory. In this paper, I derive multi-object first-moment smoothers for forward-backward smoothing through a new formulation of the p.g.fl. smoother which takes advantage of the p.g.fl. Bayes update. This formulation permits the straightforward derivation of first-moment multi-object smoothers, including the PHD smoother.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124225780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
Estimating network parameters for selecting community detection algorithms 估计网络参数，选择社区检测算法
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712065
Leto Peel
{"title":"Estimating network parameters for selecting community detection algorithms","authors":"Leto Peel","doi":"10.1109/ICIF.2010.5712065","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712065","url":null,"abstract":"This paper considers the problem of algorithm selection for community detection. The aim of community detection is to identify sets of nodes in a network which are more interconnected relative to their connectivity to the rest of the network. A large number of algorithms have been developed to tackle this problem, but as with any machine learning task there is no “one-size-fits-all” and each algorithm excels in a specific part of the problem space. This paper examines the performance of algorithms developed for weighted networks against those using unweighted networks for different parts of the problem space (parameterised by the intra/inter community links). It is then demonstrated how the choice of algorithm (weighted/unweighted) can be made based only on the observed network.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116314110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 23
Simulating fusion algorithms with gaming platforms 模拟融合算法与游戏平台
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712092
L. Lewis, Christopher Wright, Nolan DiStasio
{"title":"Simulating fusion algorithms with gaming platforms","authors":"L. Lewis, Christopher Wright, Nolan DiStasio","doi":"10.1109/ICIF.2010.5712092","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712092","url":null,"abstract":"We discuss issues in testing various cognitive fusion algorithms for situation management. We provide a proof-of-principle discussion and demo showing how gaming technologies and platforms could be used to devise and test various fusion algorithms, including input, processing, and output, and we look at how the proof-of-principle could lead to more advanced test beds and methods for high-level fusion in support of situation management. We develop four simple fusion scenarios and one more complex scenario in which a simple rule-based system is scripted to govern the behavior of battlespace entities. We conclude that the proof-of-principle warrants further work to experiment with various high-level fusion algorithms and more complex scenarios for simulation exercises.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114802120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Tracking an accelerated target with a nonlinear constant heading model 用非线性恒航向模型跟踪加速目标
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712089
Rong Yang, G. Ng, B. Ng
{"title":"Tracking an accelerated target with a nonlinear constant heading model","authors":"Rong Yang, G. Ng, B. Ng","doi":"10.1109/ICIF.2010.5712089","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712089","url":null,"abstract":"This paper proposes a nonlinear model to track a maneuvering target in acceleration motion. The acceleration motion is traditionally modeled as a linear function with the state which consists of target position, speed and acceleration in the x, y and possibly z coordinates. The state elements in different coordinate are assumed uncoupled. However, This assumption is not generally true, as the state elements in different coordinates are correlated by the common target heading. Thus, a nonlinear constant heading model is suggested in this paper. To implement this nonlinear model, a two-stage least squares method is developed for track initiation, and an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are proposed to estimate the state in track maintenance. Performance of the nonlinear model is demonstrated through simulation data, and results show that the proposed nonlinear model outperforms the traditional linear model.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124482370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Web application for time-series analysis based on particle filter available on cloud computing system 基于粒子滤波的时间序列分析Web应用程序可在云计算系统上使用
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712015
H. Nagao, T. Higuchi
{"title":"Web application for time-series analysis based on particle filter available on cloud computing system","authors":"H. Nagao, T. Higuchi","doi":"10.1109/ICIF.2010.5712015","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712015","url":null,"abstract":"We develop web application “CloCK-TiME” (Cloud Computing Kernel for Time-series Modeling Engine), which enables users to analyze their time-series data by using a networked PC cluster in a cloud computing system. This software decomposes a given multivariate time-series data into trend, seasonal, autoregressive (AR), and observation noise components, by using the particle filter (PF) algorithm. We also develop a user interface, by which users can set parameters needed in the analysis such as trend order, seasonal period, AR order, and the number of particles. We show an application example in the case of tide gauge data recorded along the coastline of Japan. We are planning to improve our analysis engine in order to obtain not only optimum model parameters but also their posterior distributions eventually by a hybrid method consisting of the PF and the MCMC algorithms.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124006501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adapting the state uncertainties of tracks to environmental constraints 使轨道状态不确定性适应环境约束
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711832
Stephan Reuter, K. Dietmayer
{"title":"Adapting the state uncertainties of tracks to environmental constraints","authors":"Stephan Reuter, K. Dietmayer","doi":"10.1109/ICIF.2010.5711832","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711832","url":null,"abstract":"In most multi-target tracking algorithms it is assumed that the movements of the targets are statistically independent of each other. This assumption may lead to predictions which are not possible due to physical exclusions. Instead of integrating the dependence between the objects directly into the tracking module, we propose to handle scenarios with interactions between the tracked object and other objects by adapting the uncertainty about the state of the object. The adaption is based on occupancy grids and reduces the uncertainty without endangering the consistency of the tracking filter.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126433290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
An imaging target tracking software for a precision guided missile application 一种用于精确制导导弹的成像目标跟踪软件
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711905
J. Bae, Sang Hoon Lee, Yong Kim, Yoon Sik Jung
{"title":"An imaging target tracking software for a precision guided missile application","authors":"J. Bae, Sang Hoon Lee, Yong Kim, Yoon Sik Jung","doi":"10.1109/ICIF.2010.5711905","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711905","url":null,"abstract":"Detection and tracking are the critical problems of computer vision. It is essential pre-processing for other algorithms. In this paper, we present an efficient and robust detection and tracking algorithm which is based on morphological operation and dynamic filtering (HPDAF: Highest Probability Data Association Filter). In airborne IR imagery, objects are usually obscure and too small to recognize their shape. Therefore dynamic filtering approach can be the best solution for tracking. Several experimental results show that our proposed algorithm efficiently detects and tracks the object regardless of size and their shape consistency. Temporarily occluded targets can be handled track-termination and re-detect sequence of the proposed algorithm.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126490785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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