Many low level vision tasks that are computationally intensive are easily parallelizable. The lack of parallel processing systems, or their prohibitive costs, have prevented the move of vision processing algorithms fr...
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Many low level vision tasks that are computationally intensive are easily parallelizable. The lack of parallel processing systems, or their prohibitive costs, have prevented the move of vision processing algorithms from single processor systems to multiprocessor systems. With the recent spurt of parallel processing hardware, there is a need to investigate the feasibility of using such machines for some vision algorithms. Speedup is an important factor in determining the feasibility of migration from single processor systems to parallel processors. In this work, we investigate a particular segmentation algorithm and present theoretical speedup results. Our formula can work out numerical speedups by simply plugging in the parameter values.< >
An empirical measure for the selection of the edge-enhancement Gaussian filter is developed. The Gaussian filter is specified by its standard deviation sigma ; the filter's spatial support is a function of sigma ....
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An empirical measure for the selection of the edge-enhancement Gaussian filter is developed. The Gaussian filter is specified by its standard deviation sigma ; the filter's spatial support is a function of sigma . An estimation procedure for sigma using Fourier analysis is described. The measure is easy to implement and is based totally on the image at hand. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support, which is needed to enhance the edges. Other equivalent bandwidth definitions can be used to obtain a measure of the frequency spread in the smoothed image (e.g., the mean-square bandwidth).< >
An optimal learning scheme is proposed for a class of bidirectional associative memories (BAMs). This scheme, based on the perceptron learning algorithm, is motivated by the inadequacies/incompleteness of the weighted...
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An optimal learning scheme is proposed for a class of bidirectional associative memories (BAMs). This scheme, based on the perceptron learning algorithm, is motivated by the inadequacies/incompleteness of the weighted learning by global optimization, as derived by Wang et al. (1993). It is shown that the new scheme has superior properties: (1) Convergence to the correct solution, when it exists; and (2) A larger basin of attraction for the given set of patterns.
Real-time monitoring of site usage in public areas subject to major crowd movements relies on human observers with limited attention span and varying reliability. It is essential to investigate techniques to acquire c...
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Real-time monitoring of site usage in public areas subject to major crowd movements relies on human observers with limited attention span and varying reliability. It is essential to investigate techniques to acquire crowd data and features automatically first, as part of the data gathering process, to develop realistic models for planning and designing pedestrian facilities in urban areas and, secondly, as online systems to detect problems in crowd movement before or shortly after they occur, using existing CCTV systems wherever possible. Such studies could lead to improved site designs, management procedures, public safety and reduced operating costs. Image processing techniques applicable to the measurement of density and motion in crowded scenes have therefore been presented. These give results comparable to human observers with potential for real-time implementation. Detailed studies of site usage and real-time operation then become feasible.< >
There is no standard representation scheme that is followed by different groups of robot designers to describe the orientation of a rotating rigid body. For a sensor-based robot, the particular rotation representation...
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There is no standard representation scheme that is followed by different groups of robot designers to describe the orientation of a rotating rigid body. For a sensor-based robot, the particular rotation representation scheme used by the robot affects not only the specification of the positioning of the arm and end-effector, but also the specification of the placement of the sensors and the method of computing the sensory-to-world transformation. Thus the need for finding the transformation between different rotation representations is obvious for one involved in the development of high-level software systems that need to be transported to different robots utilizing different rotation representation schemes. Among those representation schemes, Euler angle representations are widely used in commercial robots as well as in research laboratory robots. Typically, there are three different Euler angle representation systems, and each system describes a particular orientation of a rigid body in a reference coordinate frame by specifying three angles. Mathematical derivations of the transformation relationships underlying the parameters from two most commonly utilized representation schemes are presented. These relationships are derived in two different ways. One is based upon the solution of the inverse transform for Euler angles and the other is based upon the Napier's rules associated with spherical trigonometry.
Generalised Hermite polynomials are employed for the reconstruction of an unknown signal from a knowledge of its zero-crossings, under certain conditions on its spatial/spectral width, but dispensing with the assumpti...
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Generalised Hermite polynomials are employed for the reconstruction of an unknown signal from a knowledge of its zero-crossings, under certain conditions on its spatial/spectral width, but dispensing with the assumption of bandlimitedness. A computational implementation of the proposed method is given for one-variable (or one-dimensional) signals, featuring an application of simulated annealing for optimal reconstruction.
A custom IC processor that traces contours in black-and-white images is described. The CMOS IC contains a finite state machine, ALU, input delay line, and RAM. Each processor extracts the edges from a rectangular port...
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A custom IC processor that traces contours in black-and-white images is described. The CMOS IC contains a finite state machine, ALU, input delay line, and RAM. Each processor extracts the edges from a rectangular portion of the input image and traces the edges, outputting a description of the contours. A complete tracing system employs an array of these processors. The array architecture allows expansion to handle arbitrarily large images. The processors trace independently, thereby providing fully parallel high-speed operation. Partial contours are generated as a result of the partitioning of the image among the processors. A postprocessor links any partial contours created by the subdivision of the input image. The contour-tracing algorithm and simulation results for compression ratio and number of operations are presented. The architecture and measured performance of the IC are described.
A computational framework for an accurate, robust, and efficient stereo approach is developed. Most of the deficiencies prevailing in current computational models of stereo can be attributed to their use of a single, ...
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In this paper we nzake an attempt to bring out the rationale that, for complex robotic applications, contact sensors can provide certain vital information quite easily as compared to non-contact sensors. We begin with...
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Intelligent robots interact with the real world by employing their advanced sensory mechanisms to perceive their environment, and their effectors and tools to change the state of their environment. Such intelligent ro...
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