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Study of a modified Dempster-Shafer approach using an expected utility interval decision rule

Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 34-42页

作者： Cheaito, Ali Lecours, Michel Bosse, Eloi Universite Laval Canada

The Combination operation of the conventional Dempster-Shafer algorithm has a tendency to increase exponentially the number of propositions involved in bodies of evidence by creating new ones. The aim of this paper is to explore a 'modified Dempster-Shafer' approach of fusing identity declarations emanating from different sources which include a number of radars, IFF and ESM systems in order to limit the explosion of the number of propositions. We use a non-ad hoc decision rule based on the expected utility interval (EUI) to select the most probable object in a comprehensive Platform Data Base (PDB) containing all the possible identity values that a potential target may take. We study the effect of the redistribution of the confidence levels of the eliminated propositions which otherwise overload the real-time data fusion system; these eliminated confidence levels can in particular be assigned to ignorance, or uniformly added to the remaining propositions and the ignorance. A scenario has been selected to demonstrate the performance of our modified Dempster-Shafer method of evidential reasoning.

关键词： sensor data fusion

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Multi-spectral image fusion for visual display

Multi-spectral image fusion for visual display

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Conference on sensor fusion - architectures, algorithms, and applications iiI

作者： Peli, T Peli, E Ellis, K Stahl, R Atlantic Aerosp Elect Corp Waltham MA 02154 USA

ISBN: (纸本)0819431931

This paper describes a contrast-based monochromatic fusion process. The fusion process is aimed for on board real time application and it is based on practical and computationally efficient image processing components. The process maximizes the information content in the combined image, while retaining visual clues that are essential for navigation/piloting tasks. The method is a multi scale fusion process that provides a combination of pixel selection from a single image and a weighing of the two/multiple images. The spectral region is divided into spatial sub bands of different scales and orientations, and within each scale a combination rule for the corresponding pixels taken from the two components is applied. Even when the combination rule is a binary selection the combined fused image may have a combination of pixel values taken from the two components at various scales since it is taken at each scale. The visual band input is given preference in low scale, large features fusion. This fusion process provides a fused image better tuned to the natural and intuitive human perception. This is necessary for pilotage and navigation under stressful conditions, while maintaining or enhancing the targeting detection and recognition performance of proven display fusion methodologies. The fusion concept was demonstrated against imagery from image intensifiers and forward looking infrared sensors currently used by the U.S. Navy for navigation and targeting. The approach is easily extendible to more than two bands.

关键词： image fusion contrast visual model night pilotage

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Bio-fusion for intelligent system control

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 410-417页

作者： Norseen, John D. Kropotov, Juri D. Kremen, Inna Z. Lockheed Martin Aeronautical Co

We present a realistic neural network - the canonical cortical module - built on basic principles of cortical organization. These principles are: opponent cells principle, assembly principle, canonical cortical circuit principle and modular principle. When applied to visual images, the network explains orientational and spatial frequency filtering functions of neurons in the striate cortex. Two patterns of joint distribution of opponent cells in the inhibitory cortical layer are presented: pinwheel and circular. These two patterns provide two Gestalt descriptions of local (within the frames of one module) visual image: circle-ness and cross-ness. These modules were shown to have a power for shape detection and texture discrimination. They also provide an enhancement of signal-to-noise ratio of input images. Being modality independent, the canonical cortical module seems to be good tool for bio-fusion for intelligent system control.

关键词： Neural networks

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Automated image registration using the projective transformation model and block matching feature point pair selection

Automated image registration using the projective transforma...

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Conference on sensor fusion - architectures, algorithms, and applications iiI

作者： Schultz, RR Alford, MG Univ N Dakota Dept Elect Engn Grand Forks ND 58202 USA

ISBN: (纸本)0819431931

A subpixel-resolution image registration algorithm based on the nonlinear projective transformation model is proposed to account for camera translation, rotation, zoom, pan, and tilt. Typically, parameter estimation techniques for rigid-body transformations require the user to manually select feature point pairs between the images undergoing registration. In this research, the block matching algorithm is used to automatically select correlated feature point pairs between two images;these features are then used to calculate an iterative least squares estimate of the nonlinear projective transformation parameters. Since block matching is only capable of estimating accurate displacement vectors in image regions containing a large number of edges, inaccurate feature point pairs are statistically eliminated prior to computing the least squares parameter estimate. Convergence of the registration algorithm is generally achieved in several iterations. Simulations show that the algorithm estimates accurate integer- and subpixel-resolution registration parameters for similar sensor data sets such as intensity image sequence fi ames, as well as for dissimilar sensor images such as multimodality slices from the Visible Human Project. Through subpixel-resolution registration, integrating the registered pixels fi om a short sequence of low-resolution video fi-ames generates a high-resolution video still. Experimental results are also shown in utilizing dissimilar data registration followed by vector quantization to segment tissues from multimodality Visible Human Project image slices.

关键词： block matching image registration projective transformation sensor fusion super-resolution enhancement

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Multi-spectral image fusion for visual display

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 359-368页

作者： Peli, Tamar Peli, Eli Ellis, Ken Stahl, Robert Atlantic Aerospace Electronics Corp Waltham United States

关键词： Image processing

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Multi-level data fusion approach for gradually upgrading the performances of identity verification systems

Multi-level data fusion approach for gradually upgrading the...

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Proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iiI

作者： Verlinde, Patrick Druyts, Pascal Chollet, Gerard Acheroy, Marc Royal Military Acad/Signal and Image Cent Brussels Belgium

The aim of this paper is to propose a strategy that uses data fusion at three different levels to gradually improve the performance of an identity verification system. In a first step temporal data fusion can be used to combine multiple instances of a single (mono-modal) expert to reduce its measurement variance. If system performance after this first step is not good enough to satisfy the end-user's needs, one can improve it by fusing in a second step results of multiple experts working on the same (biometric) modality. For this approach to work, it is supposed that the respective classification errors of the different experts are (at least partially) de-correlated. Finally, if the verification system's performance after this second step is still not good enough, one will be forced to move on to the third step in which performance can be improved by using multiple experts working on different (biometric) modalities. To be useful however, these experts have to be chosen in such a way that adding the extra modalities increases the separation in the multi-dimensional modality-space between the distributions of the different populations that have to be classified by the system. This kind of level-based strategy allows to gradually tune the performance of an identity verification system to the end-user's requirements while controlling the increase of investment costs. In this paper results of several fusion modules will be shown at each level. All experiments have been performed on the same multi-modal database to be able to compare the gain in performance each time one goes up a level.

关键词： sensor data fusion

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Development of emergent processing loops as a system of systems concept

Development of emergent processing loops as a system of syst...

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Conference on sensor fusion - architectures, algorithms, and applications iiI

作者： Gainey, J Blasch, E USAF Res Lab Sensors Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

This paper describes an engineering approach toward implementing the current neuroscientific understanding of how the primate brain fuses, or integrates, "'information" in the decision-making process. We describe a System of Systems (SoS) design far improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems and show how it could be applied to biometrics security. We use the physio-associative temporal sensor integration algorithm (PATSIA) which is motivated by observed functions and interactions of the thalamus, hippocampus, and cortical structures in the brain. PATSIA utilizes signal theory mathematics to model how the human efficiently perceives and uses information from the environment. The hybrid architecture implements a possible SoS-level description of the Joint Directors of US Laboratories (JDL) for fusion Working Group's functional description involving 5 levels of fusion (i.e., Preprocessing, kinematic, situation, threat, and process refinement) and their associated definitions. This SoS architecture proposes dynamic sensor and knowledge-source integration by implementing multiple Emergent Processing Loops (EPL) for Predicting, feature Extracting, Matching, and Searching both static and dynamic databases like MSTAR's PEMS loops. Biologically, this effort demonstrates these objectives by modeling similar processes from the eyes, ears. and somatosensory channels, through the thalamus, and to the cortices as appropriate while using the hippocampus for short-term memory search and storage as necessary. The particular approach demonstrated incorporates commercially available speaker verification (simulating 1D audio/signal inputs) and face recognition (simulating 2D video/image inputs) software and hardware to collect data and extract features to the PATSIA. The PATSIA maximizes the confidence levels for target identification or verification in dynamic situations using a belief filter. The proof o

关键词： sensor data fusion

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Multi-level data fusion approach for gradually upgrading the performances of identity verification systems

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 14-25页

作者： Verlinde, Patrick Druyts, Pascal Chollet, Gerard Acheroy, Marc Royal Military Acad/Signal and Image Cent Brussels Belgium

关键词： sensor data fusion

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Temporal fusion a basic for neural plasticity in the visual pathways

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 79-90页

作者： Navabi, Homayoun Tehran Iran

Vision is an excellent example of the rich interplay between computational and biological approaches to the understanding of complex information processing tasks. Studies of biological solutions to the computational problems of vision, such as contrast masking, movement detection, orientation selectivity has created many controversies in visual neuroscience. Recent neurobiological findings suggest an experimental paradigm that gives emphasis to strategies, which rely on the combined activities of cells or cell assembly for information transforms. This new perspective explains an integrated synaptic facilitation that is contingent upon the emergent spatial and temporal properties of cell activities. The paper briefly presents a novel biologically inspired adaptive architecture that can serve for analysis of cell response dynamics to encode analog (gray scale) visual sensory data under varying conditions. The key will be the active representation of visual objects temporal characteristics, i.e., the exposures (or presentation) time and the syntactic structure to achieve invariance for the fundamental problems of scene segmentation and figure-ground separation. The basic neural mechanism is that of plastic relationship between and within participating cells or cellular groups with known receptive field organizations. Our system behavior is tested with numerous parametric psychophysical data, and the selected simulation samples predict. Only the active integration (or fusion) from multiple exposure to the sequence of sensory visual information can yield a reliable encode to extract salient features of visual objects, in partially unknown and possibly changing environments.

关键词： Neural networks

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Temporal fusion a basic for neural plasticity in the visual pathways

Temporal fusion a basic for neural plasticity in the visual ...

引用

Conference on sensor fusion - architectures, algorithms, and applications iiI

作者： Navabi, H IPM Inst Studies Thoret Phys & Math ISRF Tehran Iran

ISBN: (纸本)0819431931

Vision is an excellent example of the rich interplay between computational and biological approaches to the understanding of complex information processing tasks. Studies of biological solutions to the computational problems of vision, such as contrast masking, movement detection, orientation selectivity has created many controversies in visual neuroscience. Recent neurobiological findings suggest an experimental paradigm that gives emphasis to strategies, which rely on the combined activities of cells or cell assembly for information transforms. This new perspective explains an integrated synaptic facilitation that is contingent upon the emergent spatial and temporal properties of cell activities. The paper briefly presents a novel biologically inspired adaptive architecture that can serve for analysis of cell response dynamics to encode analog (gray scale) visual sensory data under varying conditions. The key will be the active representation of visual objects temporal characteristics, i.e., the exposures (or presentation) time and the syntactic structure to achieve invariance for the fundamental problems of scene segmentation and figure-ground separation. The basic neural mechanism is that of plastic relationship between and within participating cells or cellular groups with known receptive field organizations. Our system behavior is tested with numerous parametric psychophysical data, and the selected simulation samples predict: Only the active integration (or fusion) from multiple exposure to the sequence of sensory visual information can yield a reliable encode to extract salient features of visual objects, in partially unknown and possibly changing environments.

关键词： cell assembly active representation plasticity figure_ground separation receptive field organization

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