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International Conference on Information, Communications and Signal Processing

作者： Y.V. Venkatesh N. Rishikesh Computer Vision and Artificial Intelligence Laboratory Department of Electrical Engineering Indian Institute of Science Bangalore India Indian Institute of Science Bangalore Karnataka IN

We present a few applications of the neural active contour model described by Venkatesh Rishikesh (see International Conference on Neural Networks (ICNN-97), Houston, Texas, USA, 1997). The model, which is a neural network based on the principles of self-organization, exploits the principles of spatial isomorphism and self-organization in order to create flexible contours for characterizing shapes in images. We illustrate the versatility of the model by presenting its applications to the problems of boundary extraction, stereo vision, biomedical image analysis and digital image libraries. Only the essential ideas are described.

关键词： Active contours Image edge detection Shape Deformable models Application software computer vision Artificial neural networks Stereo vision Image motion analysis Tracking

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Eye-tracking for detection of driver fatigue

Eye-tracking for detection of driver fatigue

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International Conference on Intelligent Transportation

作者： M. Eriksson N.P. Papanikotopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA University of Minnesota Minneapolis MN US

In this paper, we describe a system that locates and tracks the eyes of a driver. The purpose of such a system is to perform detection of driver fatigue. By mounting a small camera inside the car, we can monitor the face of the driver and look for eye-movements which indicate that the driver is no longer in condition to drive. In such a case, a warning signal should be issued. This paper describes how to find and track the eyes. We also describe a method that can determine if the eyes are open or closed. The primary criterion for the successful implementation of this system is that it must be highly nonintrusive. The system should start when the ignition is turned on without having the driver initiate the system. Nor should the driver be responsible for providing any feedback to the system. The system must also operate regardless of the texture and the color of the face. It must also be able to handle diverse conditions, such as changes in light, shadows, reflections, etc.

关键词： Fatigue Eyes Face detection Accidents Face recognition Real time systems Artificial intelligence Intelligent robots Robot vision systems Laboratories

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Real-time vehicle following through a novel symmetry-based approach

Real-time vehicle following through a novel symmetry-based a...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Y. Du N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA University of Minnesota Minneapolis MN US

This paper describes a novel approach to real-time vehicle following. A scheme, called "symmetry axis detection and filtering based on symmetry constraints", is proposed and has been implemented. This scheme incorporates many elements of our research efforts in sensor-based control of mobile robots and manipulators. The proposed algorithm detects and tracks the rear portion of the exterior of a leading vehicle via a camera mounted on a vehicle that belongs to a platoon. Our scheme uses the symmetry property of the shape of most vehicles. In particular, our technique takes advantage of the stable contour symmetry instead of the intensity symmetry. An algorithm that employs a voting technique is proposed in order to detect the vertical symmetry axis of the leading vehicle. A filtering method based on symmetry constraints is performed to eliminate the pixels which do not contribute to the leading vehicle's contour. As a result of the filtering, a distinct symmetric contour is obtained. Robustness and real-time performance of the symmetry-based scheme are greatly enhanced by using an adaptive processing window, the local symmetry properties, and a filtering procedure.

关键词： Filtering Vehicle detection Robot control Mobile robots Manipulators Robot vision systems Cameras Shape Voting Robustness

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Determining the skeletal description of sparse shapes

Determining the skeletal description of sparse shapes

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IEEE International Symposium on Computational intelligence in Robotics and Automation (CIRA)

作者： R. Singh V. Cherkassky N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA Department of Electrical Engineering University of Minnesota Minneapolis MN USA

A variety of techniques in machine vision involve representation of objects by using their shape skeleton. In this paper we present a method to obtain the skeletal shape of binary images in the presence of both boundary noise and noise occurring inside object regions. We propose to obtain the skeletal shape of such images by a modified version of the Kohonen self-organizing map, implemented in a batch processing mode. The modifications allow the map to adapt to the input shape distribution. At each iteration, a competitive Hebbian rule is used to progressively compute the Delaunay triangulation of the shape. Information from the triangulation augments the map topology to yield the final skeletal shape. The batch mode implementation of the self-organizing process, allows our approach to compare very favourably, in terms of computational time, with the traditional flowthrough implementations. Encouraging experimental performance has been obtained on a variety of shapes under varying signal to noise ratios.

关键词： Shape Noise shaping Skeleton Intelligent robots machine vision computer vision Noise level Noise figure machine intelligence Robot vision systems

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A rough set approach for planner evaluation

A rough set approach for planner evaluation

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IEEE International Conference on Systems, Man and Cybernetics

作者： B.K. Sy Wang Jiaxin Pattern Analysis and Machine Intelligence Group System Design Engineering Department University of Waterloo Waterloo ONT Canada Department of Computer Science CUNY Flushing NY USA The State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China

This paper discusses a rough set approach for evaluating solutions of scheduling problems. Algorithms for solving scheduling problems are planners and the scheduling problems are modelled as constraint satisfaction problems. Conventional approach for the analysis of algorithms often focuses on the time and representational complexities, and assumes an identical cost on all operations. The proposed rough set approach augments conventional approaches for the analysis of algorithms in two ways: 1) it permits the consideration of different costs arising from different operations; and 2) it allows one to define a new utility for a complexity analysis.

关键词： Algorithm design and analysis Processor scheduling Set theory machine intelligence computer science Costs Search problems Educational institutions Pattern analysis System analysis and design

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Covariance-based approach to texture processing

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APPLIED OPTICS 1996年第5期35卷 848-853页

作者： Liu, ZQ Madiraju, SVR The authors are with the Computer Vision and Machine Intelligence Laboratory Department of Computer Science University of Melbourne Parkville Victoria 3052 Australia.

We present a simple and effective approach for texture processing that uses the eigenfeatures of local covariance measures. The covariance measures act as a texton encoder, producing texture code that is invariant to local and global textural rotations. This method uses only six features obtained from two scales of the invariant encoder to generate numerical representations for roughness, anisotropy, and other higher-order textural features. Classification results for synthetic and natural textures are presented. We discuss the effect of window sizes used at local and global scales on the performance of the classifier. (C) 1996 Optical Society of America

关键词： Anisotropy Interpolation Roughness

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A generalized Hermite pyramid for ultrasonic image analysis .2. Gallstone

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ULTRASONIC IMAGING 1996年第4期18卷 305-327页

作者： Venkatesh, YV Computer Vision and Artificial Intelligence Laboratory Department of Electrical Engineering Indian Institute of Science

This paper deals with the problem of extracting information regarding the chemical composition of stones in the human gallbladder from in vitro and in vivo B-scan ultrasonic images. The images are subjected to the Hermite pyramid decomposition technique described in Part I (Venkatesh, Y. V., Ultrasonic Imaging, 18, 261-301, 1996). In an attempt to determine the chemical composition of the gallstones, the gradients of the decomposed images are input to an unsupervised classifier. The outputs of the classifier exhibit some interesting patterns that appear to be related to the chemical composition of the gallstones contained in these images. (C) 1996 Academic Press.

关键词： gallstones Hermite polynomials image decomposition medical imaging multiscale image analysis ultrasonic image analysis unsupervised classification

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A context-driven intelligent database processing system using object-oriented fuzzy cognitive maps

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INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 1996年第9期11卷 671-689页

作者： Satur, R Liu, ZQ CVMIL—Computer Vision and Machine Intelligence Lab Department of Computer Science University of Melbourne Victoria Australia

Most data sets that describe and evolve from real-world systems are by nature semiquantitative or qualitative rather than quantitative. This can mean large variations in the significance of results that are derived from this data for decision-making processes given that the original database provides training and prototypical examples that reflect systems of events in the real world. In this article we propose a structure for a Knowledge-Based System (KBS) that is derived using significance within given contextual domains. Data that would ordinarily be classified by simple attribute classification techniques are now categorized by understanding patterns and value distributions for attributes and attribute domains that exist within rich and dense databases such as in the case of census databases double dagger and Geographic Information Systems (GIS);rich by the very number of fields and interpretations, depending on the context in which the data are to be reviewed. The structure we have implemented for capturing and structuring semiquantitative information is the Fuzzy Cognitive Map (FCM). We also reduce the number of false patterns labeled ''significant'' by incorporating the knowledge used by human experts to find significance within the data. We treat this knowledge as initial background knowledge and as a minimal set for distinguishing significance for particular attribute values within a given context. (C) 1996 John Wiley & Sons, Inc.

关键词： Knowledge based systems

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Covariance methods in computer vision

Covariance methods in computer vision

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International Conference on Signal Processing Proceedings (ICSP)

作者： Zhi-Qiang Liu S. Madiraju L. Kitchen S. Dance Australia Computer Vision and Machine Intelligence Laboratory Department of Computer Science University of Melbourne Parkville Australia

We discuss the use of covariance methods in invariant feature extraction, texture segmentation, edge detection, and surface geometry analysis. The covariance technique is used to compute local descriptors and to index roughness, anisotropy, or general textural differences. We also present a simple yet effective edge detection algorithm using a neural network which is trained by invariant features generated from covariance matrices.

关键词： computer vision Image edge detection Feature extraction Rough surfaces Surface roughness Surface texture Geometry Anisotropic magnetoresistance Neural networks Covariance matrix

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Off-line unconstrained handwritten word recognition

Off-line unconstrained handwritten word recognition

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Australian and New Zealand Conference on Intelligent Information Systems

作者： Jinhai Cai Zhi-Qiang Liu Computer Vision and Machine Intelligence Lab Department of Computer Science University of Melbourne

ISBN: (纸本)0780336674

The authors describe their system for writer independent, off-line unconstrained handwritten word recognition. First, they present a new method to automatically determine the parameters of Gabor filters to extract features from slant and tilt corrected images. An algorithm is also developed to translate 2D images to 1D domain. Finally, they propose a modified dynamic programming method with fuzzy inference to recognize words. Their initial experiments have shown encouraging results.

关键词： Handwriting recognition Feature extraction Gabor filters Inference algorithms Dynamic programming Speech recognition Data mining Image segmentation Australia computer vision

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