Constraints are mathematical mapping functions which transform from an attribute or feature space onto a score or measure of plausibility. The term plausible is used because this paper assumes one is looking to suppor...
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ISBN:
(纸本)0819407445
Constraints are mathematical mapping functions which transform from an attribute or feature space onto a score or measure of plausibility. The term plausible is used because this paper assumes one is looking to support a hypothesis rather than refute it. In this paper, a system is described which allows the algorithm developer to easily incorporate domain knowledge into an interpretation process through the graphical creation and editing of constraints. These constraints can be applied to multiple sets of data through the use of application programs. Groupings or spatial relationships such as collinearity or nearness are also attributes which may be constrained in an attempt to interpret image data. Model matches may likewise be written as constraint mappings. Primitive constraints may be combined to form compound constraints, and differing compounding weights may be assigned to primitive constraints. If these weights are written as functions dependent upon other information, the a system developed with this process can be made adaptive.
Knowledge of the bidirectional optical scatter function of surfaces comprising a 2D scene is used to predict and optimize characteristics of a digitally captured image of the scene. Mathematical expressions that descr...
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ISBN:
(纸本)0819423068;9780819423061
Knowledge of the bidirectional optical scatter function of surfaces comprising a 2D scene is used to predict and optimize characteristics of a digitally captured image of the scene. Mathematical expressions that describe certain image properties including contrast, brightness, glare, etc., are developed from the scatter functions. It is these mathematical expressions that are maximized or minimized with respect to a set of coordinates used to describe the orientation of a collimated light source and imaging system relative to the scene. In this way, it is shown how illumination can be analytically prescribed to attenuated or accentuated certain properties of digital images without the trial-and-error procedure currently in practice.
In this paper an embedded vision system and control module is introduced that is capable of controlling an unmanned four-rotor helicopter and processing live video for various law enforcement, security, military, and ...
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ISBN:
(纸本)0819464821
In this paper an embedded vision system and control module is introduced that is capable of controlling an unmanned four-rotor helicopter and processing live video for various law enforcement, security, military, and civilian applications. The vision system is implemented on a newly designed compact FPGA board (Helios). The Helios board contains a Xilinx Virtex-4 FPGA chip and memory making it capable of implementing real time visionalgorithms. A Smooth Automated intelligent Leveling daughter board (SAIL), attached to the Helios board, collects attitude and heading information to be processed in order to control the unmanned helicopter. The SAIL board uses an electrolytic tilt sensor, compass, voltage level converters, and analog to digital converters to perform its operations. While level flight can be maintained, problems stemming from the characteristics of the tilt sensor limits maneuverability of the helicopter. The embedded vision system has proven to give very good results in its performance of a number of realtime robotic visionalgorithms.
The purpose of this paper is to describe the concept and architecture for an intelligent robot system that can adapt, learn and predict the future. This evolutionary approach to the design of intelligentrobots is the...
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The purpose of this paper is to describe the concept and architecture for an intelligent robot system that can adapt, learn and predict the future. This evolutionary approach to the design of intelligentrobots is the result of several years of study on the design of intelligent machines that could adapt using computervision or other sensory inputs, learn using artificial neural networks or genetic algorithms, exhibit semiotic closure with a creative controller and perceive present situations by interpretation of visual and voice commands. This information processing would then permit the robot to predict the future and plan its actions accordingly. In this paper we show that the capability to adapt, and learn naturally leads to the ability to predict the future state of the environment which is just another form of semiotic closure. That is, predicting a future state without knowledge of the future is similar to making a present action without knowledge of the present state. The theory will be illustrated by considering the situation of guiding a mobile robot through an unstructured environment for a rescue operation. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots.
There has recently been growing interest in exploiting the concept of reasoning about function for object recognition. In a function-based approach to object recognition, recognition of an object means labeling it as ...
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ISBN:
(纸本)0819413208
There has recently been growing interest in exploiting the concept of reasoning about function for object recognition. In a function-based approach to object recognition, recognition of an object means labeling it as belonging to some category of objects according to the function that it could serve. The few function-based recognition systems which have so far been described in the literature have all assumed that the input to the problem is a pure static shape description. By `pure' shape we mean that the only object property that the systems have reasoned about is their abstract shape. By `static' shape we mean that the systems have reasoned about an object from only a single (assumed rigid) abstract shape instance. This paper discusses some of the issues which must be addressed in extending the function-based approach to handle non-shape properties (such as material properties) and dynamic shape descriptions.
We present an approach for abstracting invariant classifications of spatiotemporal patterns presented in a high-dimensionality input stream, and apply an early proof-of-concept to shift and scale invariant shape recog...
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ISBN:
(纸本)0819464821
We present an approach for abstracting invariant classifications of spatiotemporal patterns presented in a high-dimensionality input stream, and apply an early proof-of-concept to shift and scale invariant shape recognition. A model called Hierarchical Quilted Self-Organizing Map (HQSOM) is developed, using recurrent self-organizing maps (RSOM) arranged in a pyramidal hierarchy, attempting to mimic the parallel/hierarchical pattern of isocortical processing in the brain. The results of experiments are presented in which the algorithm learns to classify multiple shapes, invariant to shift and scale transformations, in a very small (7 x 7 pixel) field of view.
Classical stereo algorithms attempt to reconstruct 3D models of a scene by matching points between two images. Finding points that match is an important part of this process, and point matches are most commonly chosen...
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ISBN:
(纸本)081945561X
Classical stereo algorithms attempt to reconstruct 3D models of a scene by matching points between two images. Finding points that match is an important part of this process, and point matches are most commonly chosen as the minimum of an error function based on color or local texture. Here we motivate a probabilistic approach to this point matching problem, and provide an experimental design for the empirical measurement of the color matching error for corresponding points. We use this prior in a Bayesian scene reconstruction example, and show that we get better 3D reconstruction by not committing to a specific pixel match early in the visual processing. This allows a calibrated stereo camera to be considered as a probabilistic volume sensor --- which allows it to be more easily integrated with scene structure measurements from other kinds of sensors.
This paper describes a fuzzy logic controller (FLC) designed and implemented to control the yaw angle of a 10 kW fixed speed teetered-rotor wind turbine presently being commissioned at the University of Texas at El Pa...
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ISBN:
(纸本)0819413208
This paper describes a fuzzy logic controller (FLC) designed and implemented to control the yaw angle of a 10 kW fixed speed teetered-rotor wind turbine presently being commissioned at the University of Texas at El Paso. The technical challenge of this project is that the wind turbine represents a highly stochastic nonlinear system. The problems associated with the wind turbine yaw control are of a similar nature as those experienced with position control of high inertia equipment like tracking antenna, gun turrets, and overhead cranes. Furthermore, the wind turbine yaw controller must be extremely cost-effective and highly reliable in order to be economically viable compared to the fossil fueled power generators.
In this paper I will describe work in progress on a low cost vision-based robot designed to give primitive tours. The system is very simple, robust and efficient, and runs on a hardware platform which could be duplica...
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Attributed Fuzzy Tournaments (AFT''s) are a special type of attributed fuzzy graphs which are useful to represent uncertainties inherent to many realworld problems. A new algorithm that finds the best fuzzy ma...
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ISBN:
(纸本)0819404489
Attributed Fuzzy Tournaments (AFT''s) are a special type of attributed fuzzy graphs which are useful to represent uncertainties inherent to many realworld problems. A new algorithm that finds the best fuzzy matching configuration between components of two Attributed Fuzzy Transitive Tournaments (AFTT''s) is proposed. The best fuzzy matching between two AFTT''s is the matching configuration between components of both AFTT''s such that the overall distance measure between two AFTT''s possesses the minimum value. Useful applications of the proposed algorithm can be found in scene matching where the nodes of an AFT represent the objects in the scene and the arcs represent the relationships among the objects. Uncertainties of the image are represented via fuzzy membership values associated with the nodes and arcs. An examples showing the usefulness of the algorithm in pattern matching is shown through image analysis. I.
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