A general framework for multiresolution visual recognition is introduced. the input is processed simultaneously at a coarse resolution throughout the image and at finer resolution within a small window. An approach fo...
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A general framework for multiresolution visual recognition is introduced. the input is processed simultaneously at a coarse resolution throughout the image and at finer resolution within a small window. An approach for controlling the movement of the high-resolution window is described which allows for the unification of a variety of data and model-driven behavioral paradigms. three modes have been implemented, one based on large unexplained areas in the data, one on conflicts in the object-model database, and one on a 2D space-filling algorithm. It is argued that this kind of multiresolution processing not only is useful in limiting the computational time, but also can be a deciding factor in making the entire vision problem a tractable and stable one. To demonstrate the approach, a class of 3D surface textures is introduced as a feature for recognition in the system considered. Surface texture recognition typically requires higher-resolution processingthan required for the extraction of the underlying surface. As an example, surface texture is used to discriminate between a ping-pong ball and a golf ball.< >
A high-speed regional labeling processor which continuously processes images from an image area sensor at the NTSC video rate, i.e., at the speed of 30 images (512*512*8 b/frame)/s is presented. An algorithm implement...
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A high-speed regional labeling processor which continuously processes images from an image area sensor at the NTSC video rate, i.e., at the speed of 30 images (512*512*8 b/frame)/s is presented. An algorithm implemented in the processor is described. Since this algorithm retains the label's linkage information in the form of simple linear list structure and not in graph structure, the hardware of the processor is very simple and has been implemented by wired logic alone.< >
A feedback concentrator for a massively parallel, multilevel image understanding architecture (IUA) is presented. A brief overview of the IUA is given. the details of the feedback concentrator mechanism, which was imp...
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A feedback concentrator for a massively parallel, multilevel image understanding architecture (IUA) is presented. A brief overview of the IUA is given. the details of the feedback concentrator mechanism, which was implemented using a custom VLSI chip, are presented. the custom chip uses a combination of circuit techniques to achieve high speed. A description of the custom VLSI concentrator chip is provided. the performance of the architecture is compared with a mesh-connected processor without the feedback mechanism for three common, low-level vision tasks and is shown to be significantly faster.< >
A high-performance partitionable parallel/pipeline architecture (P/sup 3/A) that is capable of real-time imageprocessing is discussed. the architecture consists of P disjoint pipes of L processors each, connected tog...
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A high-performance partitionable parallel/pipeline architecture (P/sup 3/A) that is capable of real-time imageprocessing is discussed. the architecture consists of P disjoint pipes of L processors each, connected together through a novel wraparound memory. Many different problem classes, including shuffle-exchange, butterfly, and tree algorithms, can be easily mapped into P/sup 3/A. the power of the architecture lies in its ability to exploit boththe spatial and temporal aspects of concurrency balancing parallelism and pipelining.< >
the authors show how the data parallel programming model can be applied to high level vision tasks needed for object recognition. the architecture and programming model of the Connection Machine System are reviewed. U...
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the authors show how the data parallel programming model can be applied to high level vision tasks needed for object recognition. the architecture and programming model of the Connection Machine System are reviewed. Utilities for representing and manipulating sets of data, the primary representation outside of the image plane, are described using communications primitives, especially segmented scans. Several algorithms for matching and evidence accumulation, which are constructed from the utilities, are compared. the techniques emphasize the use of sorting and sparse representations of space in order to limit the combinatorial processing requirements of high-level vision.< >
Issues related to the efficient embedding of interprocessor communications required by parallel implementations of intermediate-level vision tasks are discussed. the performance of alternative embeddings of the interp...
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Issues related to the efficient embedding of interprocessor communications required by parallel implementations of intermediate-level vision tasks are discussed. the performance of alternative embeddings of the interprocessor communications required by specific tasks at the intermediate level of vision has been analyzed, and quantitative results have been obtained and compared to the results of corresponding implementations on the Connection Machine. In the quantitative analysis, the cost of communication primitives supported by this machine, characteristics of the task, and parameters which are characteristic of image content are taken into account. Based on the result of this analysis, a methodology is suggested for selecting the most efficient implementation of interprocessor communications among different alternatives.< >
A segmented pipeline architecture for multiresolution, focal, array processing is presented. A buffer is introduced at each point in a pipeline computation at which changes in sample density or analysis area may take ...
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A segmented pipeline architecture for multiresolution, focal, array processing is presented. A buffer is introduced at each point in a pipeline computation at which changes in sample density or analysis area may take place. these buffers divide the pipeline into segments, each with constant data load. When active, a segment runs at its full design rate. Efficiency is maintained by switching processing elements between segments as image data flows through the system. the segmented pipeline architecture is illustrated with an application to image motion analysis.< >
An integrated vision triarchitecture, Vista, for a general-purpose computervision system is described. Vista consists of three parallel architectures. A fine-grained mesh-connected single-instruction multiple-data (S...
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An integrated vision triarchitecture, Vista, for a general-purpose computervision system is described. Vista consists of three parallel architectures. A fine-grained mesh-connected single-instruction multiple-data (SIMD) architecture is proposed to minimize the communication overhead between processing elements in existing mesh-connected architectures. A medium-grained multiple-instruction multiple-data (MIMD) architecture is proposed to alleviate the communication overhead in loosely coupled multiprocessors and the memory contention in tightly coupled multiprocessors. A coarse-grained MIMD architecture is proposed to reduce the communication and input/output (I/O) overheads in existing hypercube multiprocessors. these architectures are exploited for low-, intermediate-, and high-level computervision, respectively. Each architecture shows a performance improvement in each class. the three architectures are pipelined into Vista for a general-purpose computervision system.< >
Regularization has become an important tool for solving many ill-posed problems in approximation theory-for example, in computervision-including surface reconstruction, optical flow, and shape from shading. the autho...
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Regularization has become an important tool for solving many ill-posed problems in approximation theory-for example, in computervision-including surface reconstruction, optical flow, and shape from shading. the authors attempt to determine whether the approach taken in regularization is always the correct one, and to what extent the results of regularization are reliable. they consider as an example a case in which regularization has been used to reconstruct a surface from sparse data, and attempt to determine how strongly the height of the surface at a certain point can be relied upon. these questions are answered by defining a probability distribution on the class of surfaces considered, and computing its expectation and variance. the variance can be used, for instance, to construct a safety strip around the interpolated surface that should not be entered if collision withthe surface is to be avoided.< >
the recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of ...
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the recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of an opaque 3-D object. A large depth-of-field image is used to constrain the intensities of the voxels. the depths of voxels are estimated from a highly defocused image by using simulated annealing to solve a constrained optimization problem. It is concluded that the method provides a framework for high-resolution depth recovery from defocused images. the method is computationally-intensive; however, it is amenable to parallel processing and is well suited for small field-of-interest applications.< >
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