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International Conference on Pattern Recognition

作者： Mingrui Wu Bo Zhang Ling Zhang State key laboratory of Intelligent Technology and Systems Beijing China Department of Computer Science and Technology Tsinghua University Beijing China Artificial Intelligence Institute Anhui University of Technology Jijel Algeria

ISBN: (纸本)0769507506

In this paper, a geometrical approach for building neural networks is proposed. With the proposed approach, it is very easy to construct an efficient neural classifier to solve the handwritten Chinese character recognition problem, as well as other pattern recognition problems of large scale. Experiments are conducted to evaluate the performance of the proposed approach and results obtained are promising.

关键词： Neural networks Character recognition Pattern recognition Solid modeling Large-scale systems Handwriting recognition Neurons Laboratories intelligent systems computer science

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Online distance recovery for a sewer inspection robot

Online distance recovery for a sewer inspection robot

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International Conference on Pattern Recognition

作者： M. Kolesnik G. Baratoff Institute for Autonomous Intelligent Systems GMD-Ais Schloss Birlinghoven Sankt Augustin Germany Neural Information Processing Laboratory Department of Computer Science University of Ulm Albert-Einstein-Allee Ulm Germany

ISBN: (纸本)0769507506

An algorithm for online distance computation based on images taken in a sewer by a robot-inspector is presented. Modern concrete sewers are made of standard cylindrical pipes separated by manhole junction areas. Circular structures typically originate at the pipe ends and entrances as well as at the joints of the pipe sections. These structures provide regular marks on the sewer images and can be used for their 3D interpretation. After each robot motion, we extract these circular structures from camera images, and recover their distance relative to the robot. The use of a laser-based orientation method to ensure almost parallel viewing direction of the robot head with respect to the pipe axis drastically simplifies the necessary image processing operations. The method is applied to real image sequences taken in a sewer test-net. Our results show that pipe ends and junctions can be reliably detected by the robot. We intend to use the approach to facilitate robot navigation for sewer inspection.

关键词： Inspection Concrete Robot motion Robot vision systems Cameras Parallel robots Head Image processing Image sequences Testing

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Factorization method for multiple perspective views via iterative depth estimation

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systems and computers in Japan 2000年第13期31卷 87-95页

作者： Ueshiba, Toshio Tomita, Fumiaki Electrotechnical Laboratory Tsukuba 305-8568 Japan Department of Electrical Engineering University of Tokyo Electrotechnical Laboratory Min. of Intl. Trade and Industry Intelligent Systems Division Canada Nat. Inf. Eng. Lab. Information Processing Society Robotics Society of Japan Soc. of Instrum. Control Engineers Department of Control Engineering Osaka University CMU Department of Computer Science Information Processing Society Robotics Society of Japan

This paper proposes a factorization method that reconstructs camera motion and scene shape based on the matching of multiple images under the condition that the camera captures a perspective view. Starting from the affine projection camera model, the projection depth is iteratively estimated until the measurement matrix has rank 4. Then, the obtained measurement matrix is factorized to restore the three-dimensional information of the scene in the projection space. This approach eliminates noise sensitive processes, such as the calculation of the fundamental matrix, that are required in the factorization for the conventional perspective projection image, and a stable reconstruction is realized. Furthermore, the metric constraint in the conventional affine model is extended, and the metric constraint in the perspective projection condition is derived. It is shown that the reconstruction in Euclidean space is realized if the internal parameters of the camera are given.

关键词： Image reconstruction

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Application of a genetic algorithm in triangulation of a 3-D object surface

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International Journal of computers and Applications 2000年第2期22卷 73-77页

作者： Zhenyu, Chen Mbede, J.B. Yan, Zhou Dehua, Li Hanping, Hu State Commn. Res. Open Lab. Image P. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Intelligent Contr. and Robotics Lab. Dept. of Contr. Sci. and Engineering Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Second Artillery Institute Huazhong Univ. of Sci. and Technol. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. Second Artillery Institute China Wuhan University China Artificial Intelligence Department University of Edinburgh Inst. of AI and Pattern Recognition Huazhong Univ. of Sci. and Technol. China Cogn. Sci. Natl. Key Found. Res. P. Douala University Cameroon Tübingen University Germany Automatic Control Laboratory Darmstadt University Department of Service Cameroon Min. of National Education Robotics Laboratory Huazhong Univ. of Sci. and Technol. Wuhan China Assoc. Connectionnistes These-ACTH Rennes France IEEE Soc. of Robotics and Automation IEEE Society of Control Systems IASTED Assoc. Jeunes Chercheurs Robotique France Navy University of Engineering China Huazhong Univ. of Sci. and Technol. China Department of Computer Science Airforce Radar Acad. of Engineering China Inst. of P.R and AI Huazhong Univ. of Sci. and Technol.

This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.

关键词： Object recognition

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On generalisation of machine learning with neural-evolutionary computations 3

On generalisation of machine learning with neural-evolutiona...

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3rd International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 1999

作者： Kumar, Rajeev Department of Computer Science Centre for Robotics and Intelligent Systems Birla Institute of Technology and Science Pilani333 031 India

ISBN: (纸本)0769503004

Generalisation is a non-trivial problem in machine learning and more so with neural networks which have the capabilities of inducing varying degrees of freedom. It is influenced by many factors in network design, such as network size, initial conditions, learning rate, weight decay factor, pruning algorithms, and many more. In spite of continuous research efforts, we could not arrive at a practical solution which can offer a superior generalisation. We present a novel approach for handling complex problems of machine learning. A multiobjective genetic algorithm is used for identifying (near-) optimal subspaces for hierarchical learning. This strategy of explicitly partitioning the data for subsequent mapping onto a hierarchical classifier is found both to reduce the learning complexity and the classification time. The classification performance of various algorithms is compared and it is argued that the neural modules are superior for learning the localised decision surfaces of such partitions and offer better generalisation. © 1999 IEEE.

关键词： Degrees of freedom (mechanics)

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On generalisation of machine learning with neural-evolutionary computations

On generalisation of machine learning with neural-evolutiona...

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International Conference on Computational Intelligence and Multimedia Applications

作者： R. Kumar Department of Computer Science Centre for Robotics & Intelligent Systems Birla Institute of Technology and Science Pilani India

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The independent components of characters are 'strokes' 5

The independent components of characters are 'strokes'

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5th International Conference on Document Analysis and Recognition, ICDAR 1999

作者： Srinivasan, S.H. Ramakrishnan, K.R. Bhagavathy, S. Institute for Robotics and Intelligent Systems Bangalore560 001 India Department of Electrical Engineering Indian Institute of Science Bangalore560 001 India Karnataka Regional Engineering College Suratkal India

ISBN: (纸本)0769503187

What are the natural features of handwritten characters and how to arrive at them automatically? We apply independent components analysis on handwritten characters. Independent components analysis extracts the underlying statistically independent signals from a mixture of them. We expect strokes to be the independent components of handwritten characters. Our findings show that stroke-like features emerge as a result of the analysis confirming the above intuition. This finding is significant since it gives automatic procedures for extracting stroke-like features from multilingual character data sets. We use these features for handwritten digit recognition using a very simple classifier. The classifier is chosen to be simple so that the quality of the input feature set can be evaluated. The recognition results indicate that the features arrived at by independent component analysis are useful. © 1999 IEEE.

关键词： Independent component analysis

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State estimation of an autonomous helicopter using Kalman filtering

State estimation of an autonomous helicopter using Kalman fi...

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Proceedings 1999 IEEE/RSJ International Conference on intelligent Robots and systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289)

作者： Myungsoo Jun S.I. Roumeliotis G.S. Sukhatme Department of Electrical Engineering-Systems USA Department of Computer Science Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA

Presents a technique to accurately estimate the state of a robot helicopter using a combination of gyroscopes, accelerometers, inclinometers and GPS. Simulation results of state estimation of the helicopter are presented using Kalman filtering based on sensor modeling. The number of estimated states of helicopter is nine : three attitudes(/spl theta/,/spl phi/,/spl psi/) from the gyroscopes, three accelerations(x/spl ***/,y/spl ***/,z/spl ***/) and three positions (x, y, z) from the accelerometers. Two Kalman filters were used, one for the gyroscope data and the other for the accelerometer data. Our approach is unique because it explicitly avoids dynamic modeling of the system and allows for can elegant combination of sensor data available at different frequencies. We also describe the larger context in which this work is embedded, namely the design and implementation of an autonomous robot helicopter.

关键词： State estimation Helicopters Kalman filters Gyroscopes Accelerometers Filtering Robot sensing systems Global Positioning System Acceleration Sensor systems

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Inductive Logic Programming: 9th International Workshop, ILP-99 Bled, Slovenia, June 24-27, 1999 Proceedings 9th

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9th International Workshop on Inductive Logic Programming, ILP 1999

作者： Deroski, Sašo Flach, Peter Joef Stefan Institute Department of Intelligent Systems Jamova 39 Ljubljana Slovenia University of Bristol Department of Computer Science Merchant Venturers Building Woodland Road Bristol United Kingdom

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The independent components of characters are 'strokes'

The independent components of characters are 'strokes'

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International Conference on Document Analysis and Recognition

作者： S.H. Srinivasan K.R. Ramakrishnan Institute for Robotics and Intelligent Systems Bangalore India Department of Electrical Engineering Indian Institute of Science Bangalore India

关键词： Independent component analysis Character recognition intelligent robots Read only memory Handwriting recognition intelligent systems Educational institutions Data mining Text analysis Writing

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