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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Örsan Aytekin Mehmet Koc Ilkay Ulusoy Computer Vision and Intelligent Systems Research Laboratory Department of Electrical and Electronics Engineering Middle East Technical University Ankara Turkey

This paper proposes a new method for the classification of synthetic aperture radar (SAR) images based on a novel feature vector. The method aims at combining intensity information of pixels with spatial information and structural relationships. Unlike classical approaches which define a static neighborhood and relate spatial information for each center pixel to all the pixels within that window, the local primitives (LPs) proposed in this study provide us with an adaptive neighborhood for each pixel. LPs correspond to a certain number of layers of local homogenous connected components. Using LPs, a feature vector (local primitive pattern, LPP) is constructed for each pixel. The feature vector includes information about the sizes and contrast differences of LPs within a disk as well as the repetitive frequency of LPs outside that disk. To test the efficiency of LPP, support vector machine (SVM) classification is utilized.

关键词： Quantization Synthetic aperture radar Support vector machine classification Feature extraction Remote sensing Training

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A novel swarm intelligence algorithm and its application in solving wireless sensor networks coverage problems

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Journal of Networks 2012年第12期7卷 2037-2043页

作者： Mo, Yuanbin Liu, Jizhong Wang, Baolei Jonathan Wu, Q.M. College of Mathematics and Computer Science Guangxi University for Nationalities Nanning 530006 China School of Mechanical and Electrical Engineering Institute of Robotics of Nanchang University Nanchang University Nanchang 330031 China Department of Electrical and Computer Engineering Computer Vision and Sensing Systems Laboratory University of Windsor Windsor N9B3P4 Canada

Wireless sensor networks (WSNs) have attracted a great deal of research due to their wide-range of potential applications. Sensor deployment and coverage problems are their important issues. This article briefly introduces the principle of swarm intelligence (SI). A novel SI algorithm based on information sharing of Particle Swarm Optimization (PSO) and diversity maintenance mechanism of Artificial Immune System (AIS) is designed and the model of coverage problems is given. Its applications in solving different deterministic and random coverage problems are given. The algorithm used in obtaining maximum coverage probability with given number of sensor nodes and minimum number of sensor nodes with required coverage probability of WSNs deterministic coverage, and determining the selected sensor nodes with coverage probability and connectivity requirement of WSNs random coverage, are analyzed in detail. The simulation results show the algorithm is practical. The applications of SI on K- coverage and connectivity problems in the future are also projected in the article. © 2012 ACADEMY PUBLISHER.

关键词： Swarm intelligence

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Tunable impedance: A semi-passive approach to practical motion control of insect-inspired MAVs

Tunable impedance: A semi-passive approach to practical moti...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Hosein Mahjoubi Katie Byl Robotics Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA USA

research on insect-inspired flapping-wing micro-aerial vehicles (FWMAV) has grown steadily in the past decade, aiming to address unique challenges in morphological construction, force production, and control strategy. In particular, effective methods for motion control still remain an open problem. This paper analyzes the mechanical impedance properties of the joint and their role in rotation of the wing and force production. The results suggest that in addition to previously observed relationship between set point and drag [1], the average lift force is also related to the stiffness of the joint. Furthermore, as long as changes in impedance properties are small, net lift and drag production are almost independent. These relationships are the basis of `tunable impedance' technique, a new approach to force/motion control in FWMAVs. A simple controller designed based on this method is used to simulate various flight maneuvers. The simulated MAV demonstrates exceptional performance, even in presence of measurement noise. This technique requires a fixed stroke profile for both wings, thus allowing to use a single stroke actuator - in a real MAV - with a bandwidth as low as the frequency of flapping. Impedance actuators also prove to have low bandwidth requirements.

关键词： Force Drag Aerodynamics Impedance Joints Production Vehicles

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Impact of the quality of spatial 3D city models on sensor networks placement optimization

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Geomatica 2012年第4期66卷 291-305页

作者： Argany, Meysam Mostafavi, Mir Abolfazl Akbarzadeh, Vahab Gagné, Christian Yaagoubi, Reda Centre for Research in Geomatics Department of Geomatics Université Laval QC Canada Computer Vision and System Laboratory Department of Electrical Engineering and Computer Engineering Université Laval QC Canada Department of Geomatics Faculty of Environmental Design King Abdulaziz University Jeddah Saudi Arabia

Sensor networks are increasingly used for tracking, monitoring, and observing spatial dynamic phenomena in the real world (e.g. urban area). In order to ensure an efficient deployment of a sensor network, several optimization algorithms have been proposed in recent years. Most of these algorithms often rely on oversimplified sensor models. In addition, they do not consider information on the terrain topography, city models, and the presence of diverse obstacles in the sensing area (e.g. buildings, trees, poles). Only some of those optimization algorithms attempt to consider the terrain information in the optimization of a sensor network deployment. However, most of these algorithms consider that the spatial models used for this purpose are perfect representations of the reality and are not sensitive to the quality of the information. However, spatial models are simplified representations of a complex reality, and hence are inherently uncertain. In this paper we will investigate the impact of the spatial data quality on the optimization of a sensor network and its spatial coverage in an urban area. For this purpose, we will investigate specific implications of spatial data quality criteria for a 3D city model that will be used in sensor network optimization algorithms. Then, we will analyze the impact of some of those criteria on the estimation of sensor network coverage.!Afterwards, a case study for sensor network deployment in an urban area will be presented. This case study will demonstrate the impact of 3D city models quality on the estimation of coverage using global and local optimization algorithms. Finally, the results obtained from this experimentation will be presented and discussed.

关键词： Sensor networks

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Palmprint verification and identification using pyramidal HOG feature and fast tree based matching

Palmprint verification and identification using pyramidal HO...

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IAPR International Conference on Biometrics (ICB)

作者： Azadeh Ghandehari Mohammad Anvaripour Sima Soltanpour Department of Engineering and Technology Islamic Azad University Saveh Iran Computer Vision Research Laboratory Electrical Engineering Faculty Sahand University of Technology of Tabriz Iran

In this paper, a palmprint identification and verification approach based on Pyramidal Histograms of Oriented Gradients (PHOG) and fast tree based matching is presented. In the feature extraction stage, proposed local histograms of oriented gradient are extracted in each level or scale of the Gaussian pyramid of the palmprint. This matter helps to extract high contrast and reliable lines. In the identification stage, features of the query palmprint are extracted and identified by matching against the training database palmprints or templates with tree based matching. The tree based matching makes verification and identification fast. The proposed method is evaluated by experiments on Hong Kong PolyU palmprint database. The experimental results show that the proposed method achieves a high performance according to identification and verification rate, over 99.85% accuracy, and high identification speed, which takes less than 2 seconds.

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Coral reef mosaicking using Teardrop and Fast Image Labeling

Coral reef mosaicking using Teardrop and Fast Image Labeling

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OCEANS 2012 MTS/IEEE Yeosu Conference: The Living Ocean and Coast - Diversity of Resources and Sustainable Activities

作者： Corpuz, Francis James Naval, Prospero Capili, Eusebio Jauod, Jaylord Judilla, Roel John Soriano, Maricor Vision and Image Processing Group National Institute of Physics University of the Philippines Diliman Quezon City Philippines Department of Computer Science College of Engineering University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Special Projects Laboratory Mapua Institute of Technology Intramuros Manila Philippines

ISBN: (纸本)9781457720895

In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a boat-towable, winged hull apparatus designed to house a commercial digital camera, and 2) a mosaicking algorithm to stitch the coral reef video into mosaics for further appreciation and analysis. The captured reef video is then separated into image frames which are to be stitched sequentially using Fast Image Labeling. The overlap between image frames is estimated using Single-Step DFT, an efficient sub-pixel estimation algorithm. The estimated overlap is used to compute for the area to be added to the mosaic space. The overlapping section between succeeding image-pairs are stitched along a seam determined by a minimal-cost path using dynamic programming. The visibility of the seam boundaries is further minimized by utilizing blending on multi-resolution splines. Experimental results on automated reef mosaics creation from actual coral reef video taken using Teardrop shows the performance of the system described. The main contribution of this work is the demonstration of a rapid reef visualization system using a diverless system and commercially available, non-research-grade imaging equipment. © 2012 IEEE.

关键词： Reefs

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Coral reef mosaicking using Teardrop and Fast Image Labeling

Coral reef mosaicking using Teardrop and Fast Image Labeling

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OCEANS - Europe

作者： Francis James Corpuz Prospero Naval Eusebio Capili Jaylord Jauod Roel John Judilla Maricor Soriano Vision and Image Processing Group Instrumentation Physics Laboratory National Institute of Physics Computer Vision and Machine Intelligence Group Department of Computer Science College of Engineering University of Philippines Quezon Philippines Computer Vision and Machine Intelligence Group Department of Computer Science College of Engineering University of Philippines Quezon Philippines Mapua Robotics Center Special Projects Laboratory Institutional Laboratory Mgmt Office Mapua Institute of Technology Manila Philippines Vision and Image Processing Group Instrumentation Physics Laboratory National Institute of Physics University of Philippines Quezon Philippines

关键词： Image segmentation Sea measurements Cameras Labeling Discrete Fourier transforms Sea floor

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for Data Center Management and Cloud Computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Miniature Tri-Axial Force Sensor for Feedback in Minimally Invasive Surgery

Miniature Tri-Axial Force Sensor for Feedback in Minimally I...

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IEEE RAS & EMBS International Conference on Biomedical robotics and Biomechatronics

作者： Peter Baki Gabor Szekely Gabor Kosa Computer Vision Laboratory Department of Information Technology and Electrical Engineering Robots and BioMedical MicroSystems (RBM2S) Laboratory School of Mechanical Engineering Faculty of Engineering Tel Aviv University

ISBN: (纸本)9781457711992

A miniature tri-axial force sensor has been developed that complies with the requirements of integration into biomedical and robotic devices due to its size and accuracy. The sensor is a machined Titanium alloy body of the overall dimensions 8.6 × φ3.4 mm with semi-conductor strain gauges embedded on it. The sensing beam's size is 1 × 1 × 4.4 mm. We present here the design, calibration method and performance evaluation of our sensor. Properly calibrated, it can provide absolute resolution of 5 mN at 2 N full scale. The accuracy of the estimated angle of incidence is ± 1°. The measured magnitude of the force is within the ± 4% range of the actual one. At maximal load the accuracy of the shear angle is ± 1°.

关键词： Force Sensor Piezoresistive Tri-Axial Medical robotics Minimally Invasive Surgery

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Stochastic search strategies in 2D using agents with limited perception

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IFAC Proceedings Volumes 2012年第22期45卷 650-654页

作者： David Puljiz Maja Varga Stjepan Bogdan University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering LARICS–Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Laboratory of Intelligent Systems Ecole Polytechnique Federale de Lausanne 1015 Lausanne Switzerland

Animals use stochastic search strategies to find a potential nest or to localize the food source. Animals do not rely much on the environmental cues or their sensory inputs. Since their cognitive capabilities are rather limited, search strategies are usually simplistic and stochastic. And yet such simple search strategies result in high efficiency in finding potential targets in limited time intervals. Similar problems with perception of the environment and limited computational power and sensory inputs are observed on the mobile robots used in search scenarios. In spite of their limitations, such robotic systems usually perform deterministic search strategies which heavily depend on environmental cues and sensory input. The research question we are addressing in this paper is which stochastic search strategy has the best performance in terms of area coverage and can stochastic search strategies outperform deterministic search strategies.

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