Pub Date : 2002-07-08DOI: 10.1109/ICIF.2002.1020922
S. Paris, J. Le Cadre
The purpose of this paper is to investigate the planning of a mobile trajectory in order to use its own motion for improving its position estimation. This optimization procedure relies upon two basic ingredients: 1) a reference measurement map of the area of interest is available before departure, and 2) real time measurement sensors placed aboard the mobile. The main objective is to plan a trajectory which minimizes the localization error along the path or/and at the arrival area. The general framework of the Markov decision process coupled with an auxiliary local cost function are the basic ingredients of a sub-optimal algorithm. The quality of the optimization scheme is evaluated by deriving the posterior Cramer-Rao bounds of the non linear discrete-time system.
{"title":"Planning for terrain-aided navigation","authors":"S. Paris, J. Le Cadre","doi":"10.1109/ICIF.2002.1020922","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1020922","url":null,"abstract":"The purpose of this paper is to investigate the planning of a mobile trajectory in order to use its own motion for improving its position estimation. This optimization procedure relies upon two basic ingredients: 1) a reference measurement map of the area of interest is available before departure, and 2) real time measurement sensors placed aboard the mobile. The main objective is to plan a trajectory which minimizes the localization error along the path or/and at the arrival area. The general framework of the Markov decision process coupled with an auxiliary local cost function are the basic ingredients of a sub-optimal algorithm. The quality of the optimization scheme is evaluated by deriving the posterior Cramer-Rao bounds of the non linear discrete-time system.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116325404","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1020883
J. J. Sudano
In some information fusion processes, the incomplete information set can be naturally mapped into a belief theory information set and a Bayesian probability theory information set. For decision making, the mapping of the belief theory fusion results represented by the basic belief assignment to a probability set is accomplished via a pignistic probability transform. This article introduces the inverse pignistic probability transforms (IPPT) that map the posteriori probabilities into the belief function theories, basic belief assignments. Also introduced are two infinite classes and some finite classes of mapping the posteriori probability results to the basic belief assignment of the belief theory.
{"title":"Inverse pignistic probability transforms","authors":"J. J. Sudano","doi":"10.1109/ICIF.2002.1020883","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1020883","url":null,"abstract":"In some information fusion processes, the incomplete information set can be naturally mapped into a belief theory information set and a Bayesian probability theory information set. For decision making, the mapping of the belief theory fusion results represented by the basic belief assignment to a probability set is accomplished via a pignistic probability transform. This article introduces the inverse pignistic probability transforms (IPPT) that map the posteriori probabilities into the belief function theories, basic belief assignments. Also introduced are two infinite classes and some finite classes of mapping the posteriori probability results to the basic belief assignment of the belief theory.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117121607","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}
A novel approach is proposed, which is able to overcome several shortcomings existing in the typical distributed multi-sensor track association (MSTA) model-the sequential minimum normalized distance nearest neighbor (SMNDNN) correlation and the sequential minimum mean square error (SMMSE) fusion. By considering the mutual dependency in the track estimation errors between different sensors and using the window cumulative normalized distance (WCND) technique, this phase optimization algorithm can guarantee stability in dealing with track association, especially in a dense track environment. The experiments demonstrate that our model can efficiently resolve the MSTA, the ad hoc dense track association problem.
{"title":"A window cumulative normalized distance based phase optimization track association model","authors":"Jia-Zhou He, Guan H. Pan, Qing Cai, Yan-Li Li, Shi-Fu Chen","doi":"10.1109/ICIF.2002.1020970","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1020970","url":null,"abstract":"A novel approach is proposed, which is able to overcome several shortcomings existing in the typical distributed multi-sensor track association (MSTA) model-the sequential minimum normalized distance nearest neighbor (SMNDNN) correlation and the sequential minimum mean square error (SMMSE) fusion. By considering the mutual dependency in the track estimation errors between different sensors and using the window cumulative normalized distance (WCND) technique, this phase optimization algorithm can guarantee stability in dealing with track association, especially in a dense track environment. The experiments demonstrate that our model can efficiently resolve the MSTA, the ad hoc dense track association problem.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126871480","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1021135
D. R. Stark, J. Spall
The broad field of evolutionary computation (EC)-including genetic algorithms as a special case-has attracted much attention in the last several decades. Many bold claims have been made about the effectiveness of various EC algorithms. These claims have centered on the efficiency, robustness, and ease of implementation of EC approaches. Unfortunately, there seems to be little theory to support such claims. One key step to formally evaluating or substantiating such claims is to establish rigorous results on the rate of convergence of EC algorithms. This paper presents a computable rate of convergence for a class of ECs that includes the standard genetic algorithm as a special case.
{"title":"Computable rate of convergence in evolutionary computation","authors":"D. R. Stark, J. Spall","doi":"10.1109/ICIF.2002.1021135","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1021135","url":null,"abstract":"The broad field of evolutionary computation (EC)-including genetic algorithms as a special case-has attracted much attention in the last several decades. Many bold claims have been made about the effectiveness of various EC algorithms. These claims have centered on the efficiency, robustness, and ease of implementation of EC approaches. Unfortunately, there seems to be little theory to support such claims. One key step to formally evaluating or substantiating such claims is to establish rigorous results on the rate of convergence of EC algorithms. This paper presents a computable rate of convergence for a class of ECs that includes the standard genetic algorithm as a special case.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126242927","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1021158
A. Berman, J. Dayan
This paper deals with robust tracking of time varying signals when there are abrupt, sudden random changes in the system parameters, the sensor gains or the transducers. Robustness of the filter is achieved by introducing a parallel cooperative controller and utilizing a new nonlinear gain-tuning algorithm for the adjusting jump parameters. By the aid of this algorithm, the filter remains stable even if the varying parameters, having unknown statistics, are outside of the original linear stability region of the nominal values of these parameters, i.e., momentarily, the eigenvalues of the discrete-time linear model of the system are outside of the unit circle. To limit the noise of the output, the gain-tuning process is activated only if the differences between the two parallel outputs of the filter are over a specified threshold.
{"title":"Robust tracking with cooperative parallel controllers","authors":"A. Berman, J. Dayan","doi":"10.1109/ICIF.2002.1021158","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1021158","url":null,"abstract":"This paper deals with robust tracking of time varying signals when there are abrupt, sudden random changes in the system parameters, the sensor gains or the transducers. Robustness of the filter is achieved by introducing a parallel cooperative controller and utilizing a new nonlinear gain-tuning algorithm for the adjusting jump parameters. By the aid of this algorithm, the filter remains stable even if the varying parameters, having unknown statistics, are outside of the original linear stability region of the nominal values of these parameters, i.e., momentarily, the eigenvalues of the discrete-time linear model of the system are outside of the unit circle. To limit the noise of the output, the gain-tuning process is activated only if the differences between the two parallel outputs of the filter are over a specified threshold.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123362390","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1021195
X. Li, Keshu Zhang, Juan Zhao, Yunmin Zhu
For pt.IV see proc. 2001 International Conf on Information Fusion. .In this paper, we continue our study of optimal linear estimation fusion in. a unified, general, and systematic setting. We clarify relationships among various BLUE and WLS fusion rules with complete, incomplete, and no prior information presented in Part I before; and we quantify the effect of prior information and data on fusion performance, including conditions under which prior information or data are redundant.
{"title":"Optimal linear estimation fusion. Part V. Relationships","authors":"X. Li, Keshu Zhang, Juan Zhao, Yunmin Zhu","doi":"10.1109/ICIF.2002.1021195","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1021195","url":null,"abstract":"For pt.IV see proc. 2001 International Conf on Information Fusion. .In this paper, we continue our study of optimal linear estimation fusion in. a unified, general, and systematic setting. We clarify relationships among various BLUE and WLS fusion rules with complete, incomplete, and no prior information presented in Part I before; and we quantify the effect of prior information and data on fusion performance, including conditions under which prior information or data are redundant.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126739170","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1021217
S. Baik, P. Pachowicz
The paper presents an application of an adaptive object recognition technique to the detection and tracking of geographical features on aerial images. The paper advocates the necessity of the continuous image analysis for the classification of changing geographical features for aerial surveillance. The introduced technique includes: 1) extraction of geographical features by texture-based image analysis, 2) model learning and closed-loop model adaptation to the perceived changes in image characteristics, 3)recognition of interested target areas, and 4) a feedback reinforcement mechanism for model adaptation. Experimental results are presented for image sequences, along a path on an aerial image established for the aerial surveillance.
{"title":"Application of adaptive object recognition approach to aerial surveillance","authors":"S. Baik, P. Pachowicz","doi":"10.1109/ICIF.2002.1021217","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1021217","url":null,"abstract":"The paper presents an application of an adaptive object recognition technique to the detection and tracking of geographical features on aerial images. The paper advocates the necessity of the continuous image analysis for the classification of changing geographical features for aerial surveillance. The introduced technique includes: 1) extraction of geographical features by texture-based image analysis, 2) model learning and closed-loop model adaptation to the perceived changes in image characteristics, 3)recognition of interested target areas, and 4) a feedback reinforcement mechanism for model adaptation. Experimental results are presented for image sequences, along a path on an aerial image established for the aerial surveillance.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127249392","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1021137
R. Qiu
The adoptions of e-business, e-service, e-management, and e-process in enterprises are accelerating across all the industrial and business sectors around the world. Correspondingly, an integrated plant-wide information system for manufacturers becomes fundamental to their continuous successes when customers are able to place orders of products and/or services via the Internet. But the lack of an effective (data) link between manufacturing and the supply chain, or other office information systems prohibits many of them from deploying an integrated plant-wide information system. This paper presents an approach to the implementation of such an e-DataLink (EDL), which facilitates system integration between manufacturing and office planning. By incorporating the concept of Virtual Production Lines (VPL) into the EDL, the computations of the EDL become information-centric rather than process-centric, resulting in delivering shop floor data to office planning in the right context at right time. In addition, using the XML technology a generic data format for system information (such as tasks, statuses of equipment, consumables, and products) will be employed in the EDL. The use of the well-recognized universal data exchange language and appropriate data fusion framework makes system integration much easier, practical, and cost-effective.
{"title":"A data fusion framework for an integrated plant-wide information system","authors":"R. Qiu","doi":"10.1109/ICIF.2002.1021137","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1021137","url":null,"abstract":"The adoptions of e-business, e-service, e-management, and e-process in enterprises are accelerating across all the industrial and business sectors around the world. Correspondingly, an integrated plant-wide information system for manufacturers becomes fundamental to their continuous successes when customers are able to place orders of products and/or services via the Internet. But the lack of an effective (data) link between manufacturing and the supply chain, or other office information systems prohibits many of them from deploying an integrated plant-wide information system. This paper presents an approach to the implementation of such an e-DataLink (EDL), which facilitates system integration between manufacturing and office planning. By incorporating the concept of Virtual Production Lines (VPL) into the EDL, the computations of the EDL become information-centric rather than process-centric, resulting in delivering shop floor data to office planning in the right context at right time. In addition, using the XML technology a generic data format for system information (such as tasks, statuses of equipment, consumables, and products) will be employed in the EDL. The use of the well-recognized universal data exchange language and appropriate data fusion framework makes system integration much easier, practical, and cost-effective.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125144779","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1021200
Peilin Lan, Q. Ji, C. Looney
In this paper, we introduce a probabilistic model based on Bayesian networks (BNs) for inferring human fatigue by integrating information from various visual cues and certain relevant contextual information. First, we briefly review the modern physiological and behavioral studies on human fatigue to identify the major causes for human fatigue and the significant factors affecting fatigue. These factors are then extracted from those studies and form the contextual information variables in our fatigue model. Visual parameters, typically characterizing the cognitive states of a person including parameters related to eyelid movement, gaze, head movement, and facial expression, serve as the sensory observations in the fatigue model. The fatigue model is subsequently parameterized based on the statistics extracted from recent studies on fatigue and on our subjective knowledge. Such a model provides mathematically coherent and sound basis for systematically aggregating visual evidences from different sources, augmented with relevant contextual information. The inference results produced by running the fatigue model using Microsoft BNs engine MSBNX demonstrate the utility of the proposed framework for predicting and modeling fatigue.
{"title":"Information fusion with Bayesian networks for monitoring human fatigue","authors":"Peilin Lan, Q. Ji, C. Looney","doi":"10.1109/ICIF.2002.1021200","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1021200","url":null,"abstract":"In this paper, we introduce a probabilistic model based on Bayesian networks (BNs) for inferring human fatigue by integrating information from various visual cues and certain relevant contextual information. First, we briefly review the modern physiological and behavioral studies on human fatigue to identify the major causes for human fatigue and the significant factors affecting fatigue. These factors are then extracted from those studies and form the contextual information variables in our fatigue model. Visual parameters, typically characterizing the cognitive states of a person including parameters related to eyelid movement, gaze, head movement, and facial expression, serve as the sensory observations in the fatigue model. The fatigue model is subsequently parameterized based on the statistics extracted from recent studies on fatigue and on our subjective knowledge. Such a model provides mathematically coherent and sound basis for systematically aggregating visual evidences from different sources, augmented with relevant contextual information. The inference results produced by running the fatigue model using Microsoft BNs engine MSBNX demonstrate the utility of the proposed framework for predicting and modeling fatigue.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123647184","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 : 2002-07-08DOI: 10.1109/ICIF.2002.1020946
L. Osadciw, P. Varshney, K. Veeramachaneni
This paper discusses a multimodal biometric sensor fusion approach for controlling building access. The motivation behind using multimodal biometrics is to improve universality and accuracy of the system. A Bayesian framework is implemented to fuse the decisions received from multiple biometric sensors. The system accuracy improves for a subset of decision fusion rules. The optimal rule is a function of the error cost and a priori probability of an intruder. This Bayesian framework formalizes the design of a system that can adaptively increase or reduce the security level. This is important to systems designed for varying security needs and user access requirements. The additional biometric modes and variable error costs give the system adaptability improving system acceptability. This paper presents the framework using three different biometric systems: voice, face, and hand biometric systems.
{"title":"Improving personal identification accuracy using multisensor fusion for building access control applications","authors":"L. Osadciw, P. Varshney, K. Veeramachaneni","doi":"10.1109/ICIF.2002.1020946","DOIUrl":"https://doi.org/10.1109/ICIF.2002.1020946","url":null,"abstract":"This paper discusses a multimodal biometric sensor fusion approach for controlling building access. The motivation behind using multimodal biometrics is to improve universality and accuracy of the system. A Bayesian framework is implemented to fuse the decisions received from multiple biometric sensors. The system accuracy improves for a subset of decision fusion rules. The optimal rule is a function of the error cost and a priori probability of an intruder. This Bayesian framework formalizes the design of a system that can adaptively increase or reduce the security level. This is important to systems designed for varying security needs and user access requirements. The additional biometric modes and variable error costs give the system adaptability improving system acceptability. This paper presents the framework using three different biometric systems: voice, face, and hand biometric systems.","PeriodicalId":399150,"journal":{"name":"Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121860683","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}
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