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Correspondence of coplanar features through P2-invariant representations 2nd

引用

2nd Joint European–US Workshop on Applications of Invariance in computer vision, 1993

作者： Meer, Peter Ramakrishna, Sudhir Lenz, Reiner Department of Electrical and Computer Engineering Rutgers University P.O. Box 909 PiscatawayNJ08855-0909 United States Image Processing Laboratory Department of Electrical Engineering Linköping University LinköpingS-58183 Sweden

ISBN: (纸本)9783540582403

An algorithm for establishing the correspondence between two projectively transformed sets of coplanar points (or lines) is proposed and its performance analyzed. Five-tuples of features are represented by projective/permutation (P2) invariants which are insensitive to the order of the features in the computation. Matched five-tuples yield feature correspondence hypotheses accumulated in a contingency table. The final correspondence is extracted from the table by a greedy algorithm. Positional uncertainties of up to five pixels and the presence of outliers are tolerated. © 1994, Springer Verlag. All rights reserved.

关键词： computers

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Motion and depth perception using spatiotemporal frequency analysis

Motion and depth perception using spatiotemporal frequency a...

引用

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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Estimation of motion vector fields using tensor field filtering

Estimation of motion vector fields using tensor field filter...

引用

IEEE International Conference on image Processing

作者： C.-F. Westin H. Knutsson Department of Electrical Engineering Computer Vision Laboratory Linköping University Sweden

This paper presents a method for computation of two-dimensional motion vector fields from an image sequence. The magnitudes from a set of spatio-temporal quadrature filters are combined into a tensor description. The shape of the tensors describe locally the structure of the spatio-temporal neighbourhood and provides information about local velocity and if true flow or only normal flow is present. It is shown how normal flow estimates are combined into a true flow using linear filtering on this tensor field description.< >

关键词： Motion estimation Tensile stress image motion analysis Equations Nonlinear filters Optical filters Filtering computer vision Optical computing Laboratories

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Anisotropic diffusion pyramids for image segmentation

Anisotropic diffusion pyramids for image segmentation

引用

IEEE International Conference on image Processing

作者： S.T. Acton A.C. Bovik M.M. Crawford School of Electrical & Computer Engineering Oklahoma State University Stillwater OK USA Department of Electrical & Computer Engineering Laboratory for Vision Systems Center for Vision and Image Science Center for Space Research and Department of Mechanical Engineering University of Texas Austin Austin TX USA

We introduce the Anisotropic Diffusion Pyramid (ADP), a structure for multiresolution image processing. We also develop the ADP for use in region-based segmentation. The pyramid is constructed using the anisotropic diffusion equations, creating an efficient scale-space representation. Segmentation is accomplished using pyramid node linking. Since anisotropic diffusion preserves edge localization as the scale is increased, the region boundaries in the coarse-to-fine ADP segmentation are accurately delineated. An application to segmentation of remotely sensed data is provided. The results of ADP segmentation are compared to Gaussian-based pyramidal segmentation. The examples show that the ADP has a superior ability to subdivide the image into integral groupings, minimizing the error in boundary localization and in pixel intensity.< >

关键词： Anisotropic magnetoresistance image segmentation Smoothing methods Equations image resolution Pixel computer vision Machine vision Hemorrhaging Radiometry

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Texture segmentation using circular-Mellin operators

Texture segmentation using circular-Mellin operators

引用

IEEE International Conference on image Processing

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

Texture is an important preattentive cue in region-based segmentation of images. In this paper, we discuss the use of circular-Mellin features for segmenting an image into homogenous regions. The circular-Mellin operators represent the spectral decomposition of the image scene in the polar-log coordinate system and are invariant to both scale and orientation of the target. Coupled with the unique shift invariance property of the correlator architecture, these circular-Mellin operators can be used for rotation- and scale-invariant feature extraction. We note that while both these feature extractors have similar functional form to the Gabor functions, the distortion-invariant characteristics of the circular-Mellin operators make them preferable for texture segmentation. Segmentation results to demonstrate their salient properties are presented.< >

关键词： image segmentation Layout computer vision Correlators Feature extraction Maximum likelihood detection Filtering theory Gabor filters Nonlinear filters Pattern recognition

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Localized Radon transform-based detection of linear features in noisy images

Localized Radon transform-based detection of linear features...

引用

IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

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

This paper presents a Radon transform-based approach to the detection of linear features in images characterized by high noise levels. This approach is based on the localized Radon transform where the intensity integration is performed over short line segments rather than across the entire image. The algorithm, referred to as the feature space line detector (FSLD) algorithm, is tested on synthetic images of linear features with very high noise levels. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions or that display some curvature.< >

关键词： Feature extraction

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Real-time visual tracking using correlation techniques

Real-time visual tracking using correlation techniques

引用

IEEE Workshop on Applications of computer vision (WACV)

作者： M.W. Eklund G. Ravichandran M.M. Trivedi S.B. Marapane Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee 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 3-D 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. The correlation filter-based tracking algorithm has proved to be useful in our research in cooperative mobile robots. A visual servoing system has been implemented using this tracking algorithm for convoying of multiple mobile robots.< >

关键词： Target tracking Cameras Robot vision systems Visual servoing computer vision Adaptive filters Mobile robots Laboratories Power engineering and energy Pipelines

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Simulation and visualization of integrated sensory-motor systems

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

引用

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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Acquisition of 3D structure of selectable quality from image streams

Acquisition of 3D structure of selectable quality from image...

引用

IEEE Workshop on Applications of computer vision (WACV)

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

In this paper we present a computational approach for extracting three-dimensional structure of controllable resolution, depth of field, and accuracy, all made available at real-time speeds. This approach utilizes the spatial and the temporal gradients of the streams of images acquired using an actively controlled camera. Depending on the requirements of a particular task, appropriate parameters such as disparity value sought, the inter-frame camera displacement, and number of frames in a stream, are chosen to control the resolution, depth of field, and accuracy. The acquisition and processing of the image stream are done in real-time on a pipeline architecture based processor. Extensive experiments are presented to demonstrate the accuracy, controllability of depth of field and resolution, and ability to perform successfully in a variety of scenes. The system operated with no latency between the image acquisition and processing. The total acquisition and processing time in these experiments is in the range of 0.27 to 1.56 sec. The depth results have an accuracy of 85% to 92%.< >

关键词： Streaming media computer vision Machine vision Cameras Pipelines Spatial resolution Layout Delay Performance analysis Robot vision systems

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Representation and learning of invariance

Representation and learning of invariance

引用

IEEE International Conference on image Processing

作者： K. Nordberg G. Granlund H. Knutsson Computer Vision Laboratory Department of Electrical Engineering Linköping University Linkoping Sweden

Invariance is a very important property of features that are useful for vision. A great deal of research on this subject is going on at different labs. While invariance mechanisms can be prescribed for certain descriptors, it is our firm belief that this is not feasible for descriptors of higher level properties in general. As a consequence, these invariance mechanisms have to be learned by the vision system. In this paper, such a learning structure is proposed. A major contribution in this paper, as well as a crucial component for a successful operation, is the use of a coordinate-free information representation: the channel representation. Furthermore, each processing unit is a linear perceptron which operates on outer products of input data, implying a complex space of invariance. Two examples of how the representation can be employed are included. The examples shows an excellent separation of invariance modes, good accuracy, as well as a fast convergence.< >

关键词： computer vision Laboratories Mechanical factors Machine vision Convergence Computational complexity Stereo vision Optical sensors image motion analysis Object recognition

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