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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Chung-Chen Chen Yi Yao Anis Drira Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering & Computer Science University of Tennessee Knoxville TN USA

Due to the capacity of pan-tilt-zoom (PTZ) cameras to simultaneously cover a panoramic area and maintain high resolution imagery, researches in automated surveillance systems with multiple PTZ cameras have become increasingly important. Most existing algorithms require the prior knowledge of intrinsic parameters of the PTZ camera to infer the relative positioning and orientation among multiple PTZ cameras. To overcome this limitation, we propose a novel mapping algorithm that derives the relative positioning and orientation between two PTZ cameras based on a unified polynomial model. This reduces the dependence on the knowledge of intrinsic parameters of PTZ camera and relative positions. Experimental results demonstrate that our proposed algorithm presents substantially reduced computational complexity and improved flexibility at the cost of slightly decreased pixel accuracy, as compared with the work of Chen and Wang. This slightly decreased pixel accuracy can be compensated by consistent labeling approaches without added cost for the application of automated surveillance systems along with changing configurations and a larger number of PTZ cameras.

关键词： Surveillance Costs Robot vision systems Smart cameras Computational complexity intelligent robots Image resolution Polynomials Labeling Simultaneous localization and mapping

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Rotorcraft path following control for extended flight envelope coverage

Rotorcraft path following control for extended flight envelo...

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Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference

作者： D.Cabecinhas R.Cunha C.Silvestre Department of Electrical Engineering and Computer Science and Institute for Systems and RoboticsInstituto Superior Técnico

This paper addresses the problem of steering a quadrotor vehicle along a predefined *** problem is formulated so as to dynamically prescribe an adequate time evolution along the path and simultaneously bound the effect of position errors on the *** proposed solution consists of a nonlinear state feedback controller for thrust and torque actuations combined with a path following timing law that i)guarantees global asymptotic convergence of the path following error to zero,for a large class of three-dimensional paths,ii) ensures that the actuation does not grow unbounded as function of the position errors,and iii) allows for zero thrust actuation to be applied when the vehicle is converging to the *** results are presented to assess the performance of the proposed controller.

关键词： Rotorcraft path following control for extended flight envelope coverage

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Rut tracking and steering control for autonomous rut following

Rut tracking and steering control for autonomous rut followi...

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IEEE International Conference on systems, Man and Cybernetics

作者： Camilo Ordonez Oscar Y. Chuy Emmanuel G. Collins Xiuwen Liu Center for Intelligent Systems Control and Robotics Department of Mechanical Engineering Florida A&M University-Florida State University USA Center for Intelligent Systems Control and Robotics Department of Computer Science Florida State University Tallahassee FL USA

Ruts formed as a result of vehicle traversal on soft ground are used by expert off road drivers because they can improve vehicle safety on turns and slopes thanks to the extra lateral force they provide to the vehicle. In this paper we propose a rut detection and tracking algorithm for autonomous ground vehicles (AGVs) equipped with a laser range finder. The proposed algorithm utilizes an extended Kalman filter (EKF) to recursively estimate the parameters of the rut and the relative position and orientation of the vehicle with respect to the ruts. Simulation results show that the approach is promising for future implementation.

关键词： Land vehicles Road vehicles Vehicle safety Remotely operated vehicles Vehicle driving Force control Control systems intelligent robots Mobile robots Vehicle detection

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An introduction to the echo state network and its applications in power system

An introduction to the echo state network and its applicatio...

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2009 15th International Conference on intelligent System Applications to Power systems, ISAP '09

作者： Dai, Jing Venayagamoorthy, Ganesh K. Harley, Ronald G. Georgia Institute of Technology School of Electrical and Computer Engineering Atlanta GA 30332 United States Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla MO 65409 United States

ISBN: (纸本)9781424450985

Echo State Network (ESN) is a new type of Recurrent Neural Network (RNN) proposed in recent years. The training process of ESN is easier and requires less computational effort than regular RNN which has the same size. Due to its high modeling capability of complex dynamic system, ESN has been used in various power system applications such as power system nonlinear load modeling and true harmonic current detection, wide area monitoring, intelligent control of an Active Power Filter (APF), overhead conductor thermal dynamics identification, wind speed or water inflow forecasting, etc. This paper introduces the basic concept and the offline and online training algorithms of the ESN in detail and reviews the state of the art of ESN applications in power systems. © 2009 IEEE.

关键词： Recurrent neural networks

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MetaTutor: Analyzing self-regulated learning in a tutoring system for biology

MetaTutor: Analyzing self-regulated learning in a tutoring s...

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作者： Azevedo, Roger Witherspoon, Amy Graesser, Arthur McNamara, Danielle Chauncey, Amber Siler, Emily Cai, Zhiquiang Rus, Vasile Lintean, Mihai Department of Psychology University of Memphis Memphis TN 38152 United States Institute for Intelligent Systems University of Memphis Memphis TN 38152 United States Department of Computer Science University of Memphis Memphis TN 38152 United States

ISBN: (纸本)9781607500285

We report preliminary data of an initial laboratory study examining the effectiveness of self-regulated learning (SRL) training versus no training on learners' ability to deploy SRL processes and learn about the circulatory system with MetaTutor. MetaTutor is an intelligent tutoring system (ITS) designed to train and foster learners' SRL processes while learning about several complex human body systems. We used a mixed methodology approach and include the results of a subset of the participants (N=30) whose product and process data we have analyzed. Overall, the results indicate that the SRL training group significantly outperformed the control group. © 2009 The authors and IOS Press. All rights reserved.

关键词： computer aided instruction

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A machine learning technique to detect and predict parkinson's disease

A machine learning technique to detect and predict parkinson...

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2009 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2009

作者： Yuan, Peijiang Zhang, Bo Li, Jianmin Wang, Julei Gao, Guodong State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China TangDu Hospital Institute of Functional Brain Disorders Fourth Military Medical University Xi'an China

ISBN: (纸本)9781601321190

Parkinson's Disease (PD) is a neurological disorder that has been a hot topic worldwide. Human neurological disorders can be modeled in animals like rats and monkeys using standardized procedures that recreate specific pathogenic events and their behavioral outcomes. Different methods have been proposed to detect and verify the efficiency and effectiveness of such models. However, the inner scheme to detect and predict PD at the early stage is still a difficult problem. In this paper, a Conditional Random Fields (CRFs) based approach for PD image detection and prediction is presented. Machine learning techniques are discussed that proved to be useful in detecting and predicting PD in animal models.

关键词： Animals

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Identification and Characteristic Descriptions of Procedural Chunks

Identification and Characteristic Descriptions of Procedural...

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Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, Computation World:

作者： Jana Krivec Matej Guid Ivan Bratko Department of Intelligent systems Jožef Stefan Institute Ljubljana Slovenia Computer and Information Science Artificial Intelligent Laboratory Ljubljana Slovenia

When dealing with cognitive architecture and behavior, chunks are one of the most well known and accepted constructs. Despite that, the nature of chunks still remains very elusive, especially with understanding chunks in procedural knowledge. Our attempt is to show the existence of chunks in procedural knowledge, define them, and describe their characteristics. With this purpose in mind, we use data mining techniques. We chose the game of chess as an experimental domain, due to its complexity, well defined rules, and a standardized measure of chess-players' knowledge. Results could contribute to the understanding of human information processing and cognitive architecture. They could be beneficial for tutoring and student modeling, and may serve as a framework for knowledge-based driven AI agents.

关键词： Artificial intelligence Humans Information processing Data mining Machine learning intelligent systems Laboratories Information science computer architecture Information retrieval

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Modeling buildings for mobile robots

Modeling buildings for mobile robots

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2009 ASCE International Workshop on Computing in Civil Engineering

作者： Borkowski, A. Grabska, E. Palacz, W. Department of Intelligent Systems Institute of Fundamental Technological Research Polish Academy of Sciences 21 Swietokrzyska Str. PL-00-049 Warsaw Poland Department of Computer Design and Graphics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University 4 Reymonta Str. PL-30-059 Krakow Poland

ISBN: (纸本)9780784410523

In the near future mobile robots accomplishing such tasks as delivery of goods, assistance for handicapped people and surveillance will become increasingly available. The aim of this paper is to show the disparity that exists at present in modeling buildings for the purposes of two domains: Architecture, Engineering & Construction (AEC) and Mobile robotics (MR). Digital product and process models developed in the AEC-domain give the user a comprehensive insight into the components and functions of the building but they neglect the needs of mobile robot operating autonomously inside the building. On the other hand, researchers in the MR-domain seem to be unaware of the results achieved in the AEC area. During the last decades the main effort in MR was devoted to the autonomous navigation. This resulted in efficient and robust procedures of acquiring floor maps from sensor readings. Further progress requires the robot to understand semantics of the surrounding world. Based on our previous research in the graph-oriented support of the AEC-design, we propose a digital model of the building that will enable the robot to recognize the functionality of particular spaces, to transform CAD-based floor plans into graphs reflecting topology and function of the building, to plan the execution of tasks posed by the human operator and to navigate inside the building. © 2009 ASCE.

关键词： Mobile robots

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PBOND:Web Server for the Prediction of Proline and Non-Proline cis/trans Isomerization

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Genomics, Proteomics & Bioinformatics 2009年第3期7卷 138-142页

作者： Konstantinos P. Exarchos Themis P. Exarchos Costas Papaloukas Anastassios N. Troganis Dimitrios I. Fotiadis Unit of Medical Technology and Intelligent Information Systems Department of Computer ScienceUniversity of IoanninaIoannina 45110Greece Institute of Biomedical Research and Technology Centre for Research and Technology-Thessaly(CERETETH)Larissa 41222Greece Department of Medical Physics Medical SchoolUniversity of IoanninaIoannina 45110Greece Department of Biological Applications and Technology University of IoanninaIoannina 45110 Greece

PBOND is a web server that predicts the conformation of the peptide bond between any two amino acids. PBOND classifies the peptide bonds into one out of four classes, namely cis imide （cis-Pro）, cis amide （cis-nonPro）, trans imide （trans-Pro） and trans amide （trans-nonPro）. Moreover, for every prediction a reliability index is computed. The underlying structure of the server consists of three stages：（1） feature extraction, （2） feature selection and （3） peptide bond classification. PBOND can handle both single sequences as well as multiple sequences for batch processing. The predictions can either be directly downloaded from the web site or returned via e-mail. The PBOND web server is freely available at http：//195.251.198.21/***.

关键词： peptide bond cis/trans isomerization support vector machine

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Mining discriminative adjectives and prepositions for natural scene recognition

Mining discriminative adjectives and prepositions for natura...

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

作者： Bangpeng Yao Juan Carlos Niebles Li Fei-Fei Department of Computer Science Princeton University NJ USA Robotics and Intelligent Systems Group Universidad del Norte Colombia Department of Electrical Engineering Princeton University NJ USA

This paper presents a method that considers not only patch appearances, but also patch relationships in the form of adjectives and prepositions for natural scene recognition. Most of the existing scene categorization approaches only use patch appearances or co-occurrence of patch appearances to determine the scene categories, but the relationships among patches remain ignored. Those relationships are, however, critical for recognition and understanding. For example, a `beach' scene can be characterized by a `sky' region above `sand', and a `water' region between `sky' and `sand'. We believe that exploiting such relations between image regions can improve scene recognition. In our approach, each image is represented as a spatial pyramid, from which we obtain a collection of patch appearances with spatial layout information. We apply a feature mining approach to get discriminative patch combinations. The mined patch combinations can be interpreted as adjectives or prepositions, which are used for scene understanding and recognition. Experimental results on a fifteen class scene dataset show that our approach achieves competitive state-of-the-art recognition accuracy, while providing a rich description of the scene classes in terms of the mined adjectives and prepositions.

关键词： Layout Road transportation Image representation intelligent robots Image recognition Data mining computer science intelligent systems Histograms

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