A tutorial introduction to the subject of multisensor integration and fusion is presented. The role of multisensor integration and fusion in the operation of intelligent systems is defined in terms of the unique type ...
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A tutorial introduction to the subject of multisensor integration and fusion is presented. The role of multisensor integration and fusion in the operation of intelligent systems is defined in terms of the unique type of information multiple sensors can provide. Multisensor integration is discussed in terms of basic integration functions and multisensor fusion in terms of the different levels at which fusion can take place. Numerical examples are given to illustrate a variety of different fusion methods. Speculations concerning possible research future directions and a guide to survey and review papers in the area of multisensor integration and fusion are presented.< >
Presents a 3D object recognition system with emphasis on an optimum placement strategy for a mobile 3D range sensor. The theoretical aspects leading to the development of the 3D sensor placement paradigm are presented...
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Presents a 3D object recognition system with emphasis on an optimum placement strategy for a mobile 3D range sensor. The theoretical aspects leading to the development of the 3D sensor placement paradigm are presented and described. The authors use a triangulation type laser of range finder in which a CCD based imaging device is utilized to view a plane of laser light bounced from a sweeping mirror. The sensor characteristics are described and modeled. A set of criteria for use in constraining the possible sensor site location for future scans is presented. These constraint conditions are essential to drive the actual sensor placement algorithm for 3D object recognition.< >
A description is given of SPAR, a task planner that has been implemented on a PUMA 762. SPAR is capable of formulating manipulation plans to meet specified assembly goals; these manipulation plans include grasping and...
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A description is given of SPAR, a task planner that has been implemented on a PUMA 762. SPAR is capable of formulating manipulation plans to meet specified assembly goals; these manipulation plans include grasping and regrasping operations if they are deemed necessary for successful completion of assembly. SPAR goes beyond classical AI planners in the sense that SPAR is capable of solving geometric goals associated with high-level symbolic goals. Consequently, if a high-level symbolic goals. Consequently, if a high-level symbolic goal is on (A,B), SPAR can also entertain the geometric conditions associated with such a goal. Therefore, a simple goal such as on (A,B) may or may not be found to be feasible depending on the kinematic constraints implied by the associated geometric conditions. SPAR has available to it a user-defined repertoire of actions for solving goals and associated with each action is an uncertainty precondition that defines the maximum uncertainty in the world description that would guarantee the successful execution of that action. SPAR has been implemented as a nonlinear constraint posting planner.< >
Inversion of the Laplace integral equation, used in the laser scattering measurement of colloidal particle size distributions, presents sever numerical and experimental difficulties. In the presence of noise the varia...
Inversion of the Laplace integral equation, used in the laser scattering measurement of colloidal particle size distributions, presents sever numerical and experimental difficulties. In the presence of noise the variance of the inversion integral is infinite, indicating maximum uncertainty in the accuracy of the inversion. The regularized inversion of the Laplace intergral equation provides a convenient computational algorithm which requires no a priori knowledge of the unknown linewidth distribution. Using the eigenfunction decomposition of the Laplace kernel, the spectral properties of the regularized inversion may be seen. Regularized inversion represents a type of low pass filter which preserves the properties of the inversion spectrum at low frequencies, but provides a cutoff at a point controlled by the regularization parameter. This filtering reduces the variance of the inversion to a finite value. Regularized inversion is somewhere between optimal filtering and the abrupt truncation used in singular value decomposition and other similar methods. Two examples, a monodisperse and a bimodal linewidth distribution, are used to compare the performance of regularized inversion to that obtained through an optimal filter.
Two algorithms for depth estimation are presented. The first algorithm simply looks for the focus level that maximizes the focus measure at each image point. The second algorithm uses a Gaussian model to interpolate t...
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Two algorithms for depth estimation are presented. The first algorithm simply looks for the focus level that maximizes the focus measure at each image point. The second algorithm uses a Gaussian model to interpolate the focus measures to obtain more accurate depth estimates. The algorithms were implemented and tested on surfaces of different roughness and reflectance properties. The results indicate that the shape-from-focus method may be applied to a variety of industrial vision problems.< >
We describe a system that performs model‐based recognition of the projections of generalized cylinders, and present new results on the final classification of the feature data. Two classification methods are proposed...
This work extends our previous effort in visualizing the spatial aspect of relativistic effects, and treats the phenomenon of time dilation; an inherent temporal effect of special ***, we demonstrate through still-fra...
ISBN:
(纸本)9780897914123
This work extends our previous effort in visualizing the spatial aspect of relativistic effects, and treats the phenomenon of time dilation; an inherent temporal effect of special ***, we demonstrate through still-frame images and live animations that in observing the viewing independent time dilation, the finite light transit time involved in performing the observation makes the observed time dilation also depend on the viewing *** we introduce the physics of special relativity into ray-tracing and make time to pass as a ray travels through space, we are able to link the spatial and temporal dimensions in a fundamental and consistent way in our simulations, and generate images that reveal the spatial and temporal properties of the 4D geometry of *** exploration highlights the interplay of the imaging process and the imaged physical events in producing the final images. It reveals a richly detailed physical reality which the mathematical language of thought experiment in relatively does not directly provide.
A particular form of parallelism, called bit-parallelism, is introduced. A bit-parallel organization distributes each bit of a data item to a different processor. Bit-parallelism allows computation that is sublinear w...
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A particular form of parallelism, called bit-parallelism, is introduced. A bit-parallel organization distributes each bit of a data item to a different processor. Bit-parallelism allows computation that is sublinear with word size for such operations as integer addition, arithmetic shifts, and data moves. The implications of bit-parallelism for system architecture are analyzed. An implementation of a bit-parallel architecture based on a mesh with a bypass network is presented. Using a conservative estimate for cycle time, a Silt processor performs 64-b integer additions more than 10 times faster than the Connection Machine-2. Using current CMOS technology, a 16 M processor Silt system would be capable of nearly 500 billion 32-b adds per second. The application of the architecture to low-level vision algorithms is discussed.< >
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