2010 13th International Conference on Information Fusion最新文献_第7页

A Hidden Markov Model for urban navigation based on fingerprinting and pedestrian dead reckoning 基于指纹识别和行人航位推算的城市导航隐马尔可夫模型

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712025

J. Seitz, Thorsten Vaupel, J. Jahn, S. Meyer, J. G. Boronat, J. Thielecke

引用次数: 68

Constrained multi-object Markov decision scheduling with application to radar resource management 约束多目标马尔可夫决策调度在雷达资源管理中的应用

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712047

M. Rezaeian, W. Moran

引用次数: 5

Approximate propagation of both epistemic and aleatory uncertainty through dynamic systems 动态系统中认知不确定性和选择性不确定性的近似传播

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711831

G. Terejanu, P. Singla, T. Singh, P. Scott

{"title":"Approximate propagation of both epistemic and aleatory uncertainty through dynamic systems","authors":"G. Terejanu, P. Singla, T. Singh, P. Scott","doi":"10.1109/ICIF.2010.5711831","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711831","url":null,"abstract":"When ignorance due to the lack of knowledge, modeled as epistemic uncertainty using Dempster-Shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation method is necessary to propagate both aleatory and epistemic uncertainty. The new framework proposed here, combines both epistemic and aleatory uncertainty into a second-order uncertainty representation which is propagated through a dynamic system driven by white noise. First, a finite parametrization is chosen to model the aleatory uncertainty by choosing a representative approximation to the probability density function conditioned on epistemic variables. The epistemic uncertainty is then propagated through the moment evolution equations of the conditional probability density function. This way we are able to model the ignorance when the knowledge about the system is incomplete. The output of the system is a Dempster-Shafer structure on sets of cumulative distributions which can be combined using different rules of combination and eventually transformed into a singleton cumulative distribution function using Smets' pignistic transformation when decision making is needed.","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":"122495248","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

Description of the Choquet Integral for tactical knowledge representation 战术知识表示的Choquet积分描述

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711844

T. Schuck, Erik Blasch

引用次数: 22

Distributed Federated Sensor Network 分布式联邦传感器网络

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711974

Ran Xu, Shuanghua Yang

引用次数: 3

Multi-Hypothesis Tracking and fusion techniques for multistatic active sonar systems 多假设跟踪和多静态主动声纳系统融合技术

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711949

Kathrin Seget, A. Schulz, U. Heute

引用次数: 7

Continuous belief functions and α-stable distributions 连续信念函数与α-稳定分布

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711934

A. Fiche, Arnaud Martin, J. Cexus, A. Khenchaf

引用次数: 6

Robust infrared vehicle tracking across target pose change using L1 regularization 基于L1正则化的目标姿态变化鲁棒红外车辆跟踪

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711902

Haibin Ling, Li Bai, Erik Blasch, Xue Mei

{"title":"Robust infrared vehicle tracking across target pose change using L1 regularization","authors":"Haibin Ling, Li Bai, Erik Blasch, Xue Mei","doi":"10.1109/ICIF.2010.5711902","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711902","url":null,"abstract":"In this paper, we propose a robust vehicle tracker for Infrared (IR) videos motivated by the recent advance in compressive sensing (CS). The new eL1-PF tracker solves a sparse model representation of moving targets via L1 regularized least squares. The sparse-model solution addresses real-world environmental challenges such as image noises and partial occlusions. To further improve tracking performance for frame-to-frame sequences involving large target pose changes, two extensions to the original L1 tracker are introduced (eL1). First, in the particle filter (PF) framework, pose information is explicitly modelled into the state space which significantly improves the effectiveness of particle sampling and propagation. Second, a probabilistic template update scheme is designed, which helps alleviating drift caused by a target pose change. The proposed tracker, named eL1-PF tracker, is tested on IR sequences from the DARPA Video Verification of Identity (VIVID) dataset. Promising results from the eL1-PF tracker are observed in these experiments in comparison with previous mean-shift and original L1-regularization trackers.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"1 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":"129758995","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: 68

Gaussian Mixture initialization in passive tracking applications 被动跟踪应用中的高斯混合初始化

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711980

M. Daun, R. Kaune

引用次数: 17

Tractor: A framework for soft information fusion 拖拉机:软信息融合框架

2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711896

Mark Prentice, Michael Kandefer, S. Shapiro

引用次数: 23