Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408078
P. Aarabi, Jerry Chi-Ling Lam, Arezou Keshavarz
The fundamental point of this paper is that the fusion of several simple, somewhat unreliable, and somewhat inefficient frontal face detectors results in an efficient and reliable frontal face detector which, without any training, performs similarly to a state-of-the-art neural network based face detector trained on 60,000 images. The simple detectors used include a skin detector, symmetry detectors, as well as structural face detectors. On a test set of 30 color images containing frontal faces, the fused face detector had an accuracy of 93% with a RMSE of 4.96 pixels, as compared to an accuracy of 87% and a RMSE of 8.00 pixels for the neural network based face detector. On the Caltech face database, the fused face detector had a 90% detection rate which is on par with state-of-the-art face detection methods that utilize extensive prior training, including the neural network approach which achieves a detection rate of 94%.
{"title":"Face detection using information fusion","authors":"P. Aarabi, Jerry Chi-Ling Lam, Arezou Keshavarz","doi":"10.1109/ICIF.2007.4408078","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408078","url":null,"abstract":"The fundamental point of this paper is that the fusion of several simple, somewhat unreliable, and somewhat inefficient frontal face detectors results in an efficient and reliable frontal face detector which, without any training, performs similarly to a state-of-the-art neural network based face detector trained on 60,000 images. The simple detectors used include a skin detector, symmetry detectors, as well as structural face detectors. On a test set of 30 color images containing frontal faces, the fused face detector had an accuracy of 93% with a RMSE of 4.96 pixels, as compared to an accuracy of 87% and a RMSE of 8.00 pixels for the neural network based face detector. On the Caltech face database, the fused face detector had a 90% detection rate which is on par with state-of-the-art face detection methods that utilize extensive prior training, including the neural network approach which achieves a detection rate of 94%.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114841259","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408158
J. Aughenbaugh, Brian R. LaCour
This paper examines the ordering of measurement updates for a general Bayesian inference problem and its impact on the estimation of the posterior distribution. The approach used compares the expected improvement to the posterior from various types of potential measurements, taking into account the current estimated prior but not the actual measurements, to determine the optimal measurement to perform and/or incorporate. The expected improvement is quantified using both an entropy and a covariance-based measure, each of which is further approximated for computational expedience. Compared to a random ordering of measurements, the posterior is observed to converge more quickly, resulting in a significant improvement in performance.
{"title":"Measurement prioritization for optimal Bayesian fusion","authors":"J. Aughenbaugh, Brian R. LaCour","doi":"10.1109/ICIF.2007.4408158","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408158","url":null,"abstract":"This paper examines the ordering of measurement updates for a general Bayesian inference problem and its impact on the estimation of the posterior distribution. The approach used compares the expected improvement to the posterior from various types of potential measurements, taking into account the current estimated prior but not the actual measurements, to determine the optimal measurement to perform and/or incorporate. The expected improvement is quantified using both an entropy and a covariance-based measure, each of which is further approximated for computational expedience. Compared to a random ordering of measurements, the posterior is observed to converge more quickly, resulting in a significant improvement in performance.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128023184","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408084
X. Li
Many problems involve joint decision and estimation, where qualities of decision and estimation affect each other. This paper proposes an integrated approach based on a new Bayes risk, which is a generalization of those for decision and estimation separately. Theoretical results of the optimal joint decision and estimation that minimizes the new Bayes risk are presented. The power of the new approach is illustrated by applications in target tracking and classification.
{"title":"Optimal bayes joint decision and estimation","authors":"X. Li","doi":"10.1109/ICIF.2007.4408084","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408084","url":null,"abstract":"Many problems involve joint decision and estimation, where qualities of decision and estimation affect each other. This paper proposes an integrated approach based on a new Bayes risk, which is a generalization of those for decision and estimation separately. Theoretical results of the optimal joint decision and estimation that minimizes the new Bayes risk are presented. The power of the new approach is illustrated by applications in target tracking and classification.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125484858","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408009
B. Zeng, Jun Wei, Tao Hu
It is a critical consideration to collect and fuse sensed information in an energy efficient manner for obtaining a long lifetime of the sensor network. Based on our findings that the conventional methods of direct transmission, shortest path routing, and Dempster-Shafer tool may not be optimal for data fusion of sensor networks, we propose LEECF (low-energy event centric fusion), a event-centric-based protocol that utilizes the centric sensor node to aggregate the event data among the triggered sensors in a short delay. LEECF incorporates a fast information fusion into the routing protocol to reduce the amount of information that must be transmitted to the sink and the time complexity of fusion computation of fusion center. Simulations show that LEECF can decrease the energy and fusion time significantly compared with conventional routing protocols and D-S evidence theory with the increased number of sensors.
{"title":"An energy-efficient data fusion protocol for wireless sensor network","authors":"B. Zeng, Jun Wei, Tao Hu","doi":"10.1109/ICIF.2007.4408009","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408009","url":null,"abstract":"It is a critical consideration to collect and fuse sensed information in an energy efficient manner for obtaining a long lifetime of the sensor network. Based on our findings that the conventional methods of direct transmission, shortest path routing, and Dempster-Shafer tool may not be optimal for data fusion of sensor networks, we propose LEECF (low-energy event centric fusion), a event-centric-based protocol that utilizes the centric sensor node to aggregate the event data among the triggered sensors in a short delay. LEECF incorporates a fast information fusion into the routing protocol to reduce the amount of information that must be transmitted to the sink and the time complexity of fusion computation of fusion center. Simulations show that LEECF can decrease the energy and fusion time significantly compared with conventional routing protocols and D-S evidence theory with the increased number of sensors.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121933368","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408208
É. Bossé, A. Jousselme, P. Maupin
Defence Research and Development Canada at Valcartier is pursuing the exploration of situation analysis concepts and the prototyping of computer-based decision support systems to maintain the state of situational awareness for the decision maker. The integration of the human element at the beginning of the analysis process is an important facet of our approach. The mathematical formalism and methodology proposed will be illustrated on concrete examples for visibility-based terrain analysis and reasoning for combat search and rescue (CSAR) operations. The work presented is based on the North Atlantis scenario GIS dataset, depicting a conflict taking place over an imaginary continent. The dataset is composed of topographic, hydrographical, transportation, and other typical land cover layers. Applications presented will include landing site determination as well as shortest path to crash site determination.
{"title":"Situation analysis for decision support: A formal approach","authors":"É. Bossé, A. Jousselme, P. Maupin","doi":"10.1109/ICIF.2007.4408208","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408208","url":null,"abstract":"Defence Research and Development Canada at Valcartier is pursuing the exploration of situation analysis concepts and the prototyping of computer-based decision support systems to maintain the state of situational awareness for the decision maker. The integration of the human element at the beginning of the analysis process is an important facet of our approach. The mathematical formalism and methodology proposed will be illustrated on concrete examples for visibility-based terrain analysis and reasoning for combat search and rescue (CSAR) operations. The work presented is based on the North Atlantis scenario GIS dataset, depicting a conflict taking place over an imaginary continent. The dataset is composed of topographic, hydrographical, transportation, and other typical land cover layers. Applications presented will include landing site determination as well as shortest path to crash site determination.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122247809","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4407978
Li Bai, S. Biswas, Erik Blasch
This paper presents a new probabilistic approach to determine survivability of reconfigurable systems as a system-level performance metric in an operational environment. In contrast to known methods of estimating survivability in terms of susceptibility and vulnerability, the proposed method (1) includes directional threats on various subsystems into the analysis and (2) provides a framework for operational information fusion processes to better sustain unpredictable or hostile environmental disturbances. In this paper, we distinguish the survivability and reliability metrics, where we demonstrate the importance of survivability metric in a dynamic information fusion process for an operational environment. We present our main result using a piping system of fluid flow; however, the concept easily extends to other flow systems, such as power networks, computer communication networks, and military reconfigurable information systems, etc. Survivability of these large scale reconfigurable networks depend on their capability of assessing directional threats, situation awareness, and their ability to dynamically adapt to new configurations. The proposed survivability method embedded in an information fusion environment can be used for real time dynamic reconfiguration of large scale systems, optimization and routing of data and information, and detect and mitigate hardware and software threats.
{"title":"Survivability - An information fusion process metric from an operational perspective","authors":"Li Bai, S. Biswas, Erik Blasch","doi":"10.1109/ICIF.2007.4407978","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4407978","url":null,"abstract":"This paper presents a new probabilistic approach to determine survivability of reconfigurable systems as a system-level performance metric in an operational environment. In contrast to known methods of estimating survivability in terms of susceptibility and vulnerability, the proposed method (1) includes directional threats on various subsystems into the analysis and (2) provides a framework for operational information fusion processes to better sustain unpredictable or hostile environmental disturbances. In this paper, we distinguish the survivability and reliability metrics, where we demonstrate the importance of survivability metric in a dynamic information fusion process for an operational environment. We present our main result using a piping system of fluid flow; however, the concept easily extends to other flow systems, such as power networks, computer communication networks, and military reconfigurable information systems, etc. Survivability of these large scale reconfigurable networks depend on their capability of assessing directional threats, situation awareness, and their ability to dynamically adapt to new configurations. The proposed survivability method embedded in an information fusion environment can be used for real time dynamic reconfiguration of large scale systems, optimization and routing of data and information, and detect and mitigate hardware and software threats.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121767881","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408039
M. Lefrancois, B. Topp, M. Gammon, Robert Stuart
Defence R&D Canada - Atlantic's Networked Underwater Warfare technology demonstration project is conducting a trial to investigate the potential for enhanced effectiveness in producing an underwater common operating picture under field conditions. The trial consists of nodes including ships, aircraft, submarines and additional reach back to shore support centres. The trial objectives are threefold; as a vehicle to develop fusion technologies, as a means to improve underwater warfare effectiveness and to demonstrate that faster formation of the underwater common operating picture can be produced using networked shared information. One of the products that has been developed is the Networked Enabled Combat System (NECS).
{"title":"Networked enabled combat for the enhancement of the underwater common operating picture","authors":"M. Lefrancois, B. Topp, M. Gammon, Robert Stuart","doi":"10.1109/ICIF.2007.4408039","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408039","url":null,"abstract":"Defence R&D Canada - Atlantic's Networked Underwater Warfare technology demonstration project is conducting a trial to investigate the potential for enhanced effectiveness in producing an underwater common operating picture under field conditions. The trial consists of nodes including ships, aircraft, submarines and additional reach back to shore support centres. The trial objectives are threefold; as a vehicle to develop fusion technologies, as a means to improve underwater warfare effectiveness and to demonstrate that faster formation of the underwater common operating picture can be produced using networked shared information. One of the products that has been developed is the Networked Enabled Combat System (NECS).","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115964379","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408012
Kathryn B. Laskey, P. Costa, Edward J. Wright, K. Laskey
In a net-centric world, systems will be required to fuse data from geographically dispersed, heterogeneous information sources operating asynchronously, to produce up-to-date, mission-relevant knowledge to inform commanders. Realizing this vision requires overcoming a number of technical challenges. Among these is the need for semantic interoperability among systems with different internal data models and vocabularies. Ontologies are seen as a key enabling technology for semantic interoperability. Although information fusion by nature involves reasoning under uncertainty, traditional ontology formalisms provide no principled means of reasoning under uncertainty. This paper proposes the use of probabilistic ontologies within a service-oriented architecture as a means to enable semantic interoperability in net-centric fusion systems.
{"title":"Probabilistic ontology for net-centric fusion","authors":"Kathryn B. Laskey, P. Costa, Edward J. Wright, K. Laskey","doi":"10.1109/ICIF.2007.4408012","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408012","url":null,"abstract":"In a net-centric world, systems will be required to fuse data from geographically dispersed, heterogeneous information sources operating asynchronously, to produce up-to-date, mission-relevant knowledge to inform commanders. Realizing this vision requires overcoming a number of technical challenges. Among these is the need for semantic interoperability among systems with different internal data models and vocabularies. Ontologies are seen as a key enabling technology for semantic interoperability. Although information fusion by nature involves reasoning under uncertainty, traditional ontology formalisms provide no principled means of reasoning under uncertainty. This paper proposes the use of probabilistic ontologies within a service-oriented architecture as a means to enable semantic interoperability in net-centric fusion systems.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132421451","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408110
J. Rezaie, B. Moshiri, A. Rafati, Babak Nadjar Araabi
In this paper, first an enhanced neuro-fuzzy method for modeling nonlinear system is presented In this method we use EM algorithm for identification of local models, which gain us model mismatch covariance. The achieved model can be stated in state space model as a linear time-varying system. As the noise and model mismatch covariance is known, Kalman filter can be easily used for centralized estimation fusion. The simulations show that using centralized estimation fusion will enhance the estimation accuracy to a great deal.
{"title":"Modified LOLIMOT algorithm for nonlinear centralized Kalman filtering fusion","authors":"J. Rezaie, B. Moshiri, A. Rafati, Babak Nadjar Araabi","doi":"10.1109/ICIF.2007.4408110","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408110","url":null,"abstract":"In this paper, first an enhanced neuro-fuzzy method for modeling nonlinear system is presented In this method we use EM algorithm for identification of local models, which gain us model mismatch covariance. The achieved model can be stated in state space model as a linear time-varying system. As the noise and model mismatch covariance is known, Kalman filter can be easily used for centralized estimation fusion. The simulations show that using centralized estimation fusion will enhance the estimation accuracy to a great deal.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134264803","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}
Pub Date : 2007-07-09DOI: 10.1109/ICIF.2007.4408190
M. Mirmomeni, B. Moshiri, C. Lucas
Nowadays, there are considerable attentions to combined classifier. Recently, the focus has been shifting from practical heuristic solutions of combination methods to give a methodological way of design. In this study a co-evolutionary algorithm is presented for this purpose. The algorithm synthesizes an explicit classifier directly from bserved data produced by intelligently generated tests. The algorithm is composed of two co-evolving populations; one population evolves candidate classifiers. The second population evolves informative tests that either extract new information from the pattern or elicit desirable behavior from it The fitness of candidate classifiers is their ability to classify in response to all tests carried out so far; the fitness of candidate tests is their ability to make the classifiers disagree in their classifications. The generality of this modeling-evaluation algorithm is demonstrated by applying the chosen classifier of this algorithm to identify modulation methods and results depict the power of this algorithm.
{"title":"Modulation identification using combined classifiers and co-evolution of classifiers and tests","authors":"M. Mirmomeni, B. Moshiri, C. Lucas","doi":"10.1109/ICIF.2007.4408190","DOIUrl":"https://doi.org/10.1109/ICIF.2007.4408190","url":null,"abstract":"Nowadays, there are considerable attentions to combined classifier. Recently, the focus has been shifting from practical heuristic solutions of combination methods to give a methodological way of design. In this study a co-evolutionary algorithm is presented for this purpose. The algorithm synthesizes an explicit classifier directly from bserved data produced by intelligently generated tests. The algorithm is composed of two co-evolving populations; one population evolves candidate classifiers. The second population evolves informative tests that either extract new information from the pattern or elicit desirable behavior from it The fitness of candidate classifiers is their ability to classify in response to all tests carried out so far; the fitness of candidate tests is their ability to make the classifiers disagree in their classifications. The generality of this modeling-evaluation algorithm is demonstrated by applying the chosen classifier of this algorithm to identify modulation methods and results depict the power of this algorithm.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131799978","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：