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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： H.P. Gadagkar M.M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

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Multi-primitive hierarchical (MPH) stereo system

Multi-primitive hierarchical (MPH) stereo system

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Conference on computer vision and Pattern Recognition (CVPR)

作者： S.B. Marapane M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

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, typically edge-element-based, primitive for stereo analysis and to their use of a single-level control strategy. The multi-primitive hierarchical (MPH) framework for stereo analysis presented is directed toward overcoming these deficiencies. In the MPH model, stereo analysis is performed in multiple stages, incorporating multiple primitives and utilizing a hierarchical control strategy. The higher levels of the hierarchical system are based on primitives containing more semantic information, and the results of stereo analysis at higher levels are used for guidance at the lower levels. It is shown that such a stereo system is superior to a single-level, single-primitive system.< >

关键词： Stereo vision computer vision Laboratories Robustness Computational modeling Performance analysis Layout Contracts Algorithm design and analysis Robot vision systems

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Optimal nonlinear pattern restoration from noisy binary figures

Optimal nonlinear pattern restoration from noisy binary figu...

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1992 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 1992

作者： Schonfeld, D. Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois at Chicago ChicagoIL60680-4348 United States

ISBN: (纸本)0818628553

A mathematical framework for the solution of statistical inference problems on a class of random sets is proposed. It is based on a new definition of expected pattern. The least-mean-difference estimator (restoration filter) is proved, under certain conditions, to be equivalent to the minimization of the measure of size (area) of the set-difference between the original pattern and the expected pattern of the estimated (restored) pattern. Consequently, it is proved that, under certain conditions, if the estimator (restoration filter) is unbiased, then it is the least mean difference estimator (restoration filter). © 1992 IEEE.

关键词： Restoration

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Simulation and graphical interface for programming and visualization of sensor-based robot operation

Simulation and graphical interface for programming and visua...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： C.X. Chen M.M. Trivedi C.R. Bidlack Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA Artificial Intelligence Laboratory College of Engineering University of Michigan Ann Arbor MI USA

The authors describe a simulation environment which can be of utility in the design, development, and operation of sensor-driven robotic systems. This environment incorporates the ability to simulate sensory inputs and their effects on the planning and control functions. A detailed design of the simulator is presented. The simulator is integrated within an entire robotic system, and is utilized for automatic robot programming. Alternatively, the simulated system operation flow can be controlled through either a teach mode or a program mode. Five sensing modalities can be simulated: proximity, point laser range, ultrasonic range, laser range depth imagery, and edge-based intensity imagery. The simulation and animation of a particular robot is described. The unique features of the simulator are that it simulates and utilizes sensory information feedback, it integrates planning and simulation, and it makes the switching between real and simulation mode in the robotic system transparent to the user.< >

关键词： Robot programming Visualization Robot sensing systems Robotics and automation Computational modeling Robot vision systems Automatic control Animation computer simulation Software safety

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Biologically-based control of omnidirectional leg coordination

Biologically-based control of omnidirectional leg coordinati...

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1992 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 1992

作者： Ayers, J. Crisman, J. Marine Science Center Department of Biology Northeastern University East Point NahantMA01908 United States Robotic and Vision Systems Laboratory Dept of Electrical and Computer Engineering Northeastern University BostonMA02115 United States

ISBN: (纸本)0780307372

Animals have been engineered by evolution to adapt and survive in a dynamic environment. We are studying the neural control mechanisms of the American lobster and applying the resultant neurophysiological models to robot control. Our long term goal is to study the utility of biological models to robot control for an underwater walking machine. Our robot architecture is based on a well accepted biological model that includes command systems, coordinating systems, and central pattern generation. We focus, in this paper, on the central pattern generator and coordinating systems. The central pattern generator controls the motion of the leg appropriate to walking directions with and without sensory feedback. The coordinating systems control the gait pattern of the legs. We have built a simulator which models the central pattern generator and coordination and demonstrates basic walking motions of the leg in any direction and at multiple speeds. We also simulate the coordination of a stable gait. Our future research includes testing our simulated results on an eight legged walking machine based on the morphology of the lobster, and adding sensors, reflexes, and taxes to our robotic model. © 1992 Institute of electrical and Electronics Engineers Inc. All rights reserved.

关键词： Sensory feedback

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A Mean Field Solution to Anisotropic Edge Detection of Remotely Sensed Images

A Mean Field Solution to Anisotropic Edge Detection of Remot...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： S.T. Acton M.M. Crawford Laboratory for Vision Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Center for Space Research and Department of Mechanical Engineering University of Texas Austin Austin TX USA

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Optimal nonlinear pattern restoration from noisy binary figures

Optimal nonlinear pattern restoration from noisy binary figu...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： D. Schonfeld Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois Chicago Chicago IL USA

关键词： Noise figure Image restoration Pattern analysis Filters Set theory Signal restoration Laboratories Area measurement Size measurement Morphology

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A video pattern generator for vision test

A video pattern generator for vision test

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： M.S. Obaidat D.S. Abu-Saymeh G. Cibis D. Pierce Comput. Eng. Res. Lab. Missouri Univ. Columbia MO USA Computer Engineering Research Laboratory Department of Electrical & Computer Engineering University of Missouri Columbia USA Transoft Limited Kansas City MO USA

A hardware and software system for the generation of video patterns that can be used for various vision tests, particularly depth perception, is presented. Among the capabilities of the system is generation of static and dynamic random dot stereograms that can be used to test depth perception. The system generates the patterns in real time, which provides the ability of moving the objects in the stereogram. The system is based on the TMS34010 graphics processor, operating at 40 MHz. The processor is interfaced to 512 Kb of video random access memory (VRAM), 256 Kb of dynamic random access memory (DRAM), and 16 Kb of erasable programmable read only memory (EPROM). The system also has an RS-232C serial communication part for communicating with a host computer and a red, green, and blue (RGB) video output for connection to an RGB color video monitor which displays the various video patterns. The software developed produces the various patterns and test experiments. A monitor program was also written to aid in developing any new software needed to produce new patterns or test experiments.< >

关键词： Test pattern generators Software testing System testing Random access memory EPROM computer displays computerized monitoring Hardware Software systems Real time systems

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SENSOR-DRIVEN INTELLIGENT ROBOTICS

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ADVANCES IN computerS 1991年第C期32卷 105-148页

作者： TRIVEDI, MM CHEN, CX Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department The University of Tennessee Knoxville Tennessee

Intelligent robotic systems should be capable of performing a range of complex tasks in unstructured and dynamic environments. This chapter discusses a number of important items associated with intelligent robots, role of vision sensing in intelligent robotics, and architecture for the design of an intelligent robot. The chapter also describes the computational task hierarchy that governs a model-based robot vision system, and presents a detailed tutorial on two important components of this hierarchy: image segmentation and matching. The main capabilities that intelligent robotic systems should possess include ability for perception of their environment, planning of their actions, and execution of the planned action. The two important components of a model-based vision system are image segmentation and the matching module. A procedure that allows transformation of 2D image coordinates into 3D world coordinates is also discussed in the chapter. The architecture and control aspects of an integrated sensor-based robotic system consist of six modules: supervisor, task planner, perception, motor, user interface, and knowledge-base. Intelligent, sensor-driven systems pose many challenging basic-research problems from a broad range of scientific and technological disciplines; however, there are many important application areas where such systems would be of significant value and utility, including hazardous environments such as nuclear plants, underwater, and space as well as many industrial-automation tasks. Recent advancements in the VLSI, computer-architectures, sensor-and robot-hardware, and artificial-intelligence fields may aid to the development of robust, practical, and cost-effective intelligent robotic systems for a wide variety of applications.

关键词： Robotics

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Localized measurement of image fractal dimension using gabor filters

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Journal of Visual Communication and Image Representation 1991年第2期2卷 114-128页

作者： Super, Boaz J. Bovik, Alan C. Department of Computer Sciences The University of Texas at Austin Austin TX 78712 United States Laboratory for Vision Systems Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 United States

We present a method for making accurate, optimally localized measurements of the fractal dimension of images modeled as locally fractal Brownian surfaces. Fractal Brownian surfaces are good models for the multiscale and irregular image textures arising from natural scenes and for elevation maps of terrain. To obtain accurate local values of the fractal dimension, spatio-spectrally localized measurements are necessary. Our method employs Gabor filters, which optimize the conflicting goals of spatial and spectral localization as constrained by the functional uncertainty principle. The outputs from multiple Gabor filters are fitted to a fractal power-law curve whose parameters determine the fractal dimension. The algorithm produces a local value of the fractal dimension at every point in the image. We also introduce a variational technique for enforcing a smoothness constraint on the computed fractal dimension function. This technique is implemented using an iterative relaxation algorithm. We demonstrate the method on synthetic images, real images of natural textures, and U.S. Geo-Data digital elevation maps of real terrain. We discuss the ways in which real images depart from the fractal Brownian surface model. © 1991.

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