2017 20th International Conference on Information Fusion (Fusion)最新文献_第3页

Stochastic integration Student's-t filter 随机积分学生t滤波器

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009741

O. Straka, J. Duník

引用次数: 19

The estimation fusion and Cramer-Rao bounds for nonlinear systems with uncertain observations 具有不确定观测值的非线性系统的估计融合和Cramer-Rao界

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009668

Ping Wang, Zhiguo Wang, Xiaojing Shen, Yunmin Zhu

引用次数: 2

Evidence combination for a large number of sources 大量来源的证据组合

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009759

Kuang Zhou, Arnaud Martin, Q. Pan

{"title":"Evidence combination for a large number of sources","authors":"Kuang Zhou, Arnaud Martin, Q. Pan","doi":"10.23919/ICIF.2017.8009759","DOIUrl":"https://doi.org/10.23919/ICIF.2017.8009759","url":null,"abstract":"The theory of belief functions is an effective tool to deal with the multiple uncertain information. In recent years, many evidence combination rules have been proposed in this framework, such as the conjunctive rule, the cautious rule, the PCR (Proportional Conflict Redistribution) rules and so on. These rules can be adopted for different types of sources. However, most of these rules are not applicable when the number of sources is large. This is due to either the complexity or the existence of an absorbing element (such as the total conflict mass function for the conjunctive-based rules when applied on unreliable evidence). In this paper, based on the assumption that the majority of sources are reliable, a combination rule for a large number of sources, named LNS (stands for Large Number of Sources), is proposed on the basis of a simple idea: the more common ideas one source shares with others, the more reliable the source is. This rule is adaptable for aggregating a large number of sources among which some are unreliable. It will keep the spirit of the conjunctive rule to reinforce the belief on the focal elements with which the sources are in agreement. The mass on the empty set will be kept as an indicator of the conflict. Moreover, it can be used to elicit the major opinion among the experts. The experimental results on synthetic mass functions verify that the rule can be effectively used to combine a large number of mass functions and to elicit the major opinion.","PeriodicalId":148407,"journal":{"name":"2017 20th International Conference on Information Fusion (Fusion)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128354398","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

On orientation estimation using iterative methods in Euclidean space 欧几里得空间中基于迭代方法的方向估计

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009830

Martin A. Skoglund, Zoran Sjanic, M. Kok

引用次数: 6

Extended multispectral face presentation attack detection: An approach based on fusing information from individual spectral bands 扩展多光谱人脸呈现攻击检测:一种基于各个光谱波段信息融合的方法

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009749

Ramachandra Raghavendra, K. Raja, S. Venkatesh, C. Busch

{"title":"Extended multispectral face presentation attack detection: An approach based on fusing information from individual spectral bands","authors":"Ramachandra Raghavendra, K. Raja, S. Venkatesh, C. Busch","doi":"10.23919/ICIF.2017.8009749","DOIUrl":"https://doi.org/10.23919/ICIF.2017.8009749","url":null,"abstract":"Multispectral face recognition systems are widely used in various access control applications. The vulnerability of multispectral face recognition sensors towards low-cost Presentation Attack Instrument (PAI) such as printed photos used in attacks has emerged as a serious security threat. In this paper, we present a novel framework to detect presentation attacks against an extended multispectral face sensor. The proposed framework stems from the idea of exploring the complementary information available from different bands of an extended multispectral face sensor. To this extent, two different frameworks are proposed where the first framework is based on image fusion and the second builds on the Presentation Attack Detection (PAD) score level fusion. Extensive experiments are carried out on the extended multispectral face sensor database comprising of 50 subjects with two different presentation attacks generated using the printed photo artefacts. The obtained results indicate the superior performance of the PAD score level fusion on detecting both known and unknown attacks.","PeriodicalId":148407,"journal":{"name":"2017 20th International Conference on Information Fusion (Fusion)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130169494","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: 15

Multi-sensor image fusion based on fourth order partial differential equations 基于四阶偏微分方程的多传感器图像融合

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009719

D. P. Bavirisetti, G. Xiao, Gang Liu

{"title":"Multi-sensor image fusion based on fourth order partial differential equations","authors":"D. P. Bavirisetti, G. Xiao, Gang Liu","doi":"10.23919/ICIF.2017.8009719","DOIUrl":"https://doi.org/10.23919/ICIF.2017.8009719","url":null,"abstract":"In this paper, a new image fusion algorithm based on fourth order partial differential equations and principal component analysis is introduced. This is for the first time fourth order partial differential equations brought into the context of image fusion. The proposed algorithm is as follows: First, fourth order partial differential equations are applied on each source image to obtain approximation and detail images. Second, principal component analysis is applied on detail images to obtain optimal weights. Third, final detail image is obtained by fusing these detail images with help of optimal weights. Fourth, final approximation image is obtained by employing an average operation on approximation images. Finally, resultant fused image is calculated by combining the final approximation and detail images. Experiments are conducted on standard fusion datasets. Results are analyzed with help of petrovic metrics and further compared with traditional and recent fusion methods. Results justify that performance of the proposed method is superior to state-of-the-art fusion methods. Moreover, reasonable computational time, easy and effective implementation of the proposed method makes it suitable for real time applications.","PeriodicalId":148407,"journal":{"name":"2017 20th International Conference on Information Fusion (Fusion)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134039443","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: 164

Obstacles detection method of vehicles based on image analysis 基于图像分析的车辆障碍物检测方法

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009657

Xiang Yi, Bingjian Wang

引用次数: 0

Preference fusion and Condorcet's paradox under uncertainty 不确定条件下偏好融合与孔多塞悖论

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009636

Yiru Zhang, Tassadit Bouadi, Arnaud Martin

{"title":"Preference fusion and Condorcet's paradox under uncertainty","authors":"Yiru Zhang, Tassadit Bouadi, Arnaud Martin","doi":"10.23919/ICIF.2017.8009636","DOIUrl":"https://doi.org/10.23919/ICIF.2017.8009636","url":null,"abstract":"Facing an unknown situation, a person may not be able to firmly elicit his/her preferences over different alternatives, so he/she tends to express uncertain preferences. Given a community of different persons expressing their preferences over certain alternatives under uncertainty, to get a collective representative opinion of the whole community, a preference fusion process is required. The aim of this work is to propose a preference fusion method that copes with uncertainty and escape from the Condorcet paradox. To model preferences under uncertainty, we propose to develop a model of preferences based on belief function theory that accurately describes and captures the uncertainty associated with individual or collective preferences. This work improves and extends the previous results. This work improves and extends the contribution presented in a previous work. The benefits of our contribution are twofold. On the one hand, we propose a qualitative and expressive preference modeling strategy based on belief-function theory which scales better with the number of sources. On the other hand, we propose an incremental distance-based algorithm (using Jousselme distance) for the construction of the collective preference order to avoid the Condorcet Paradox.","PeriodicalId":148407,"journal":{"name":"2017 20th International Conference on Information Fusion (Fusion)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121464910","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

A numerically stable formulation of the square root unscented Kalman filter for state estimation 一种用于状态估计的平方根无气味卡尔曼滤波器的数值稳定公式

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009711

Tino Milschewski, Jean-Francois Bariant

{"title":"A numerically stable formulation of the square root unscented Kalman filter for state estimation","authors":"Tino Milschewski, Jean-Francois Bariant","doi":"10.23919/ICIF.2017.8009711","DOIUrl":"https://doi.org/10.23919/ICIF.2017.8009711","url":null,"abstract":"The square root unscented Kalman filter was introduced to provide a more numerically robust formulation of the unscented Kalman filter and to guarantee positive semi-definiteness. The filter maintains the Cholesky factor of the covariance matrix instead of the covariance itself. Efficient linear algebra techniques, including Cholesky update and downdate, are used to predict and update the Cholesky factor over time. However, a downdated Cholesky factor may not exist due to numerical rounding and truncation. This may impose issues especially in highly dimensional state spaces or if quantities of different magnitude are involved. A failed Cholesky downdate could be accounted for by predicting a more conservative covariance matrix or by neglecting the filter step in the prevailing iteration. However, both approaches may decrease filter performance. A more sophisticated strategy would be to prevent these issues from happening in the first place. We propose a mathematically equivalent filter that numerically guarantees positive semi-definiteness for any arithmetic precision at the cost of a negligible runtime increase. It applies the auxiliary formulation of the scaled unscented transform and filters the forecast sigma points separately.","PeriodicalId":148407,"journal":{"name":"2017 20th International Conference on Information Fusion (Fusion)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122671876","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: 2

Predictive situation awareness model for smart manufacturing 智能制造预测态势感知模型

2017 20th International Conference on Information Fusion (Fusion) Pub Date : 2017-07-10 DOI: 10.23919/ICIF.2017.8009849

C. Park, Kathryn B. Laskey, S. Salim, Joongyoon Lee

{"title":"Predictive situation awareness model for smart manufacturing","authors":"C. Park, Kathryn B. Laskey, S. Salim, Joongyoon Lee","doi":"10.23919/ICIF.2017.8009849","DOIUrl":"https://doi.org/10.23919/ICIF.2017.8009849","url":null,"abstract":"Smart manufacturing relies on a combination of different sources providing key information to support diverse activities throughout the manufacturing process. Most smart manufacturing systems focus on activities directly related to the management of robots, conveyor belts, maintenance logs, and others that ensure the process runs smoothly. An initial step to support such smart manufacturing systems is an awareness process for estimating current situations and predicting future situations in manufacturing, called Predictive Manufacturing Situation Awareness (MSAW). Our research addresses developing an MSAW system with the goal of enhancing industrial competitiveness (e.g., lower cost in shorter time with higher quality) for the manufacturing industry. This requires constant monitoring of market conditions, prices of manufacturing assets, and other inputs that would help to define how the production line behaves. This input is highly stochastic, which makes fusing the data from the diverse sources a challenge. In such situations, the MSAW system requires efficient knowledge representation for various situations and expeditious reasoning methods for estimating current situations as well as predicting future situations. In this paper, we provide an overview of the data fusion process supporting MSAW, including the representation of situations with associated uncertainty, and reasoning methods to support improved manufacturing processes.","PeriodicalId":148407,"journal":{"name":"2017 20th International Conference on Information Fusion (Fusion)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123664982","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: 25