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Australian and New Zealand Conference on Intelligent Information Systems

作者： C. Pudney P. Kovesi B. Robbins Biomedical Confocal Microscopy Research Centre Department of Pharmacology University of Western Australia Nedlands WA Australia Robotics and Vision Research Group Department of Computer Science University of Western Australia Nedlands WA Australia

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by M.C. Morrone and R.A. Omens (1987) marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature profiles: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters. The filters are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency space and multiplied by the image's Fourier transform. Results are presented for real confocal images and synthetic 3D image volumes.

关键词： Detectors Microscopy computer vision Filters Data analysis Image analysis Image edge detection Convolution Frequency Fourier transforms

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Using vision-based control techniques for grasping objects

Using vision-based control techniques for grasping objects

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IEEE International Conference on Systems, Man and Cybernetics

作者： C.E. Smith N.P. Papanikolopoulous Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA University of Minnesota Minneapolis MN US Dept. of Comput. Sci. Minnesota Univ. Minneapolis MN USA

We present additions to the controlled active vision framework that focus upon the autonomous grasping of a moving object in the manipulator's workspace. Our work extends the capabilities of an eye-in-hand robotic system beyond those as a "pointer" or a "camera orienter" to provide the flexibility required to robustly interact with the environment in the presence of uncertainty. The proposed work is experimentally verified using the Minnesota Robotic Visual Tracker (MRVT) to automatically select object features, to derive estimates of unknown environmental parameters, and to supply a control vector based upon these estimates to guide the manipulator in the grasping of a moving object. The system grasps objects in the manipulator's workspace without requiring the object to follow a specific trajectory and without requiring the object to maintain a specific orientation.

关键词： Robot vision systems Manipulators robotics and automation Cameras Grippers Robustness Uncertainty Automatic control Optical distortion Artificial intelligence

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Adaptive visual tracking algorithm and real-time implementation

Adaptive visual tracking algorithm and real-time implementat...

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.W. Eklund G. Ravichandran M.M. Trivedi S.B. Marapane Computer Vision and Robotics Research Laboratory Electrical and Colmputer Engineerirrg Department University of Tennessee Knoxville TN USA University of Tennessee Knoxville Knoxville TN US Dept. of Electr. & Comput. Eng. Tennessee Univ. Knoxville TN USA

A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The minimum noise and correlation energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 Hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation.

关键词： Target tracking Cameras Robot vision systems Filters Visual servoing Image motion analysis computer vision Laboratories Power engineering and energy Pipelines

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APPROXIMATE ORTHOGONAL DISTANCE REGRESSION METHOD FOR FITTING QUADRIC SURFACES TO RANGE DATA

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PATTERN RECOGNITION LETTERS 1994年第8期15卷 781-796页

作者： CAO, XP SHRIKANDE, N HU, GZ Center for Computer Vision and Robotics Research Department of Computer Science Central Michigan University Mt. Pleasant MI 48859 USA

Fitting surfaces to 3-D data is one of the basic methods of surface description for 3-D vision. Most techniques of surface fitting proposed in the literature are ''least-squares''-based that rarely produce satisfactory results if noise level is very high or if the data points are sampled from a small area. A new approach is presented in this paper that minimizes the mean squared approximate orthogonal distances with linearization using Newton's iteration method. This approach usually yields a good fit and the algorithm is reliable and efficient for real applications. Results are reported for synthetic data and several examples of real range data. Experimental results demonstrate that the approximate orthogonal distance performs better than the least squares based methods.

关键词： RANGE DATA LEAST-SQUARES ORTHOGONAL DISTANCE REGRESSION NEWTONS METHOD SURFACE FITTING

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SIMULATION AND ANIMATION OF SENSOR-DRIVEN ROBOTS

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IEEE TRANSACTIONS ON robotics AND AUTOMATION 1994年第5期10卷 684-704页

作者： CHEN, CX TRIVEDI, MM BIDLACK, CR Computer Vision and Robotics Research Laboratory the Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA Artificial Intelligence Laboratory College of Engineering University of Michigan Ann Arbor MI USA

Most simulation and animation systems utilized in robotics are concerned with simulation of the robot and its environment without simulation of sensors. These systems have difficulty in handling robots that utilize sensory feedback in their operation. In this paper, a new design of an environment for simulation, animation, and visualization of sensor-driven robots is presented. As sensor technology advances, increasing numbers of robots are equipped with various types of sophisticated sensors. The main goal of creating the visualization environment is to aid the automatic robot programming and off-line programming capabilities of sensor-driven robots. The software system will help the users visualize the motion and reaction of the sensor-driven robot under their control program. Therefore, the efficiency of the software development is increased, the reliability of the software and the operation safety of the robot are ensured, and the cost of new software development is reduced. Conventional computer-graphics-based robot simulation and animation software packages lack of capabilities for robot sensing simulation. This paper describes a system designed to overcome this deficiency.

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

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Motion perception using spatiotemporal frequency analysis

Motion perception using spatiotemporal frequency analysis

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IEEE International Conference on Image Processing

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

Motion information is extracted by identifying the temporal signature associated with the textured objects in the scene. We present a new computational framework for motion perception. Our methodology considers spatiotemporal frequency (STF) domain analysis to extract the optical flow information. First, we show that a sequence of image frames can be used to extract the motion parameters for the different regions in a dynamic scene using the basic Fourier transform properties in the STF analysis approach. A detailed analytical description of this model to interchangably extract motion and depth parameters and results to highlight their salient properties are presented.< >

关键词： Motion analysis Spatiotemporal phenomena Image motion analysis Data mining Layout Frequency domain analysis Information analysis Fourier transforms Image analysis Image sequence analysis

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Motion and depth perception using spatiotemporal frequency analysis

Motion and depth perception using spatiotemporal frequency a...

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IEEE International Conference on Systems, Man and Cybernetics

作者： G. Ravichandran M.M. Trivedi Electrical and Computer Engineering Department Computer Vision and Robrics Research Laboratory Computer Vision and Robotics Laboratary University of Tennessee Knoxville TN USA

Motion information is extracted by identifying the temporal signature associated with the textured objects in the scene. In this paper, we present a new computational framework for motion perception. Our methodology considers spatiotemporal frequency (STF) domain analysis to extract the optical flow information. First, we show that a sequence of image frames can be used to extract the motion parameters for the different regions in a dynamic scene using the basic Fourier transform properties in the STF analysis approach. When the observer (or the camera) moves, motion is induced in the scene, and the extracted motion information can then be used to estimate the depth parameters. A detailed analytical description of this model to interchangably extract motion and depth parameters and results to highlight their salient properties are presented.< >

关键词： Motion analysis Spatiotemporal phenomena Data mining Layout Image motion analysis Frequency domain analysis Information analysis Fourier transforms Image analysis Image sequence analysis

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Coordinating motion of cooperative mobile robots through visual observation

Coordinating motion of cooperative mobile robots through vis...

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IEEE International Conference on Systems, Man and Cybernetics

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

This paper describes the development of an integrated autonomous multi-robot system, where two heterogeneous robots exhibit coordinated convoying behavior. Coordination is accomplished without any communication but by visual observation. An active perception system uses visual servoing to track the leading vehicle to determine its heading and relative distance. A fuzzy logic based real-time motion controller uses the heading to control the steering and relative distance and velocity information to adjust the speed to let the trailing robot smoothly follow the leader. A novel correlation algorithm based on minimum noise and correlation energy (MINACE) filter is used for object tracking. The MINACE based tracker is adaptive and when the tracking degrades due to the change in appearance of the leading robot a new filter is synthesized online to replace the old one. The performance and robustness of the convoying system has been verified in a series of extensive laboratory trials.< >

关键词： Mobile robots Robot kinematics Motion control Velocity control Communication system control Filters Multirobot systems Mobile communication Visual servoing Remotely operated vehicles

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Sensor based obstacle avoidance and mapping for fast mobile robots

Sensor based obstacle avoidance and mapping for fast mobile ...

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IEEE International Conference on robotics and Automation (ICRA)

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

This paper describes one aspect of a project whose goal is to move a robot in an unknown environment and find pipes to decommission. While moving through the environment a low level map, in the form of an occupancy grid, along with detailed location of pipes in the environment are obtained. This paper deals only with the low level "reflex" of obstacle avoidance that is performed while the robot moves along its path as well as some of the higher level tasks involved in path planning and robot motion in order to negotiate through a hazardous environment. The overall high level interaction with the system is made as simple and user friendly as possible using a graphical interface to control high level tasks. All low level communications and processing are transparent. The robot used for experimentation is a wheeled mobile platform equipped with many different sensors including ultrasonic range sensors and cameras. A quick and efficient obstacle avoidance algorithm has been developed using sixteen ultrasonic range sensor and one infrared proximity sensor.< >

关键词： Mobile robots Infrared sensors Robot sensing systems Path planning Robot motion Communication system control Control systems Mobile communication Robot vision systems Cameras

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Simulation and visualization of integrated sensory-motor systems

Simulation and visualization of integrated sensory-motor sys...

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IEEE Workshop on Visualization and Machine vision

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 binocular robot head, BETH, with ten degrees of freedom (DOF) has been developed for research in active vision. To complement BETH, a graphical simulation and visualization environment has also been developed. The objective of building the graphical system is to create a comprehensive design tool to design and study the dynamic behavior of sensory-motor systems and their interactions with the environment. This environment integrates perception and motor actions and features complete kinematic simulation of BETH, it's sensors and it's workspace. We demonstrate the utility of this environment in systematic and extensive experimental development of computational frameworks and algorithms for 3D active vision systems which utilizes multiple passive depth cues (stereo, vergence, and depth from focusing).< >

关键词： Visualization Head Robot sensing systems Robot vision systems computer vision Computational modeling Buildings Focusing Image analysis Machine vision

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