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Temporal fusion a basic for neural plasticity in the visual pathways

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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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-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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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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COBRA based infrastructure (CORBIS) for sensor data fusion systems

COBRA based infrastructure (CORBIS) for sensor data fusion s...

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proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iii

作者： Balci, Metin Kuru, Selahattin Software Development Cent Kocaeli Turkey

The Common Object Request Broker Architecture (COBRA) has been proven to be effective for application in the Data fusion domain. However, the benefits of this system have not yet been fully realized because of unresolved issues concerning reliability, fault-tolerance and real-time/fast enough QoS behavior of the system. In view of this, an attempt has been made to develop a domain specific environment with the commercially available standard products. The result is a COBRA based infrastructure (CORBIS) that provide interfaces and mechanisms for various applications and services.

关键词： Computer software

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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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Temporal fusion a basic for neural plasticity in the visual pathways

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

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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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sensor fusion options for ballistic missile defense interceptor applications

Sensor fusion options for ballistic missile defense intercep...

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proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iii

作者： Bjork, Charles Morris, Norman Dasarathy, Belur V. Smith, Bart Allen, Doug Prestwood, William T. Nichols Research Corp Huntsville AL United States

Critical elements of future exoatmospheric interceptor systems are intelligent processing (IP) techniques which can effectively combine sensor data from disparate sensors. This paper summarizes the impact on discrimination performance of several feature and classifier fusion techniques, which can be used as part of the overall IP approach. These techniques are implemented either within the Fused sensor Discrimination (FuSeD) Testbed, or off-line as building blocks that can be modified to assess differing fusion approaches, classifiers and their impact on interceptor requirements. Several optional approaches for combining the data at the different levels, i.e, feature and classifier levels, are discussed in this paper and a comparison of performance results is shown. Approaches yielding promising results must still operate within the timeline and memory constraints on board the interceptor. A hybrid fusion approach is implemented at the feature level through the use of feature sets input to specific classifiers (currently two classifiers are employed). The output of the fusion process contains an estimate of the confidence in the data and the discrimination decisions. The confidence in the data and decisions can be used in real time to dynamically select different sensor feature data, classifiers, or to request additional sensor data on specific objects that have not been confidently identified as 'lethal' or 'non-lethal'. However, dynamic selection requires an understanding of the impact of various combinations of feature sets and classifier options. Accordingly, the paper presents the various tools for exploring these options and illustrates their usage with data sets generated to realistically simulate the world of Ballistic Missile Defense (BMD) interceptor applications.

关键词： sensor data fusion

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

Study of a modified Dempster-Shafer approach using an expect...

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proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iii

作者： Cheaito, Ali Lecours, Michel Bosse, Eloi Universite Laval Que 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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General software design for multisensor data fusion

General software design for multisensor data fusion

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proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iii

作者： Junliang, Zhang Yuming, Zhao 54th Research Inst of Electronic Industry Shijiazhuang China

In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programming and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

关键词： Computer software

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