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2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012

作者： Kostavelis, Ioannis Nalpantidis, Lazaros Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Vas. Sofias 12 GR-67100 Xanthi Greece Computer Vision and Active Perception Lab. Centre for Autonomous Systems Royal Institute of Technology - KTH SE-100 44 Stockholm Sweden

ISBN: (纸本)9781457717741

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems. © 2012 IEEE.

关键词： Object recognition

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Traffic observation and situation assessment

Traffic observation and situation assessment

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15th International Workshop on Theoretical Foundations of computer vision

作者： Reulke, Ralf Rueß, Dominik Manthey, Kristian Luber, Andreas Humboldt-Universität Zu Berlin Computer Vision Unter den Linden 6 10099 Berlin Germany DLR German Aerospace Center Institute of Robotics and Mechatronics 12489 Berlin Germany DLR German Aerospace Center Institute of Transportation Systems Rutherfordstr. 2 12489 Berlin Germany

ISBN: (纸本)9783642340901

Utilization of camera systems for surveillance tasks (e. g. traffic monitoring) has become a standard procedure and has been in use for over 20 years. However, most of the cameras are operated locally and data analyzed manually. Locally means here a limited field of view and that the image sequences are processed independently from other cameras. For the enlargement of the observation area and to avoid occlusions and non-accessible areas multiple camera systems with overlapping and non-overlapping cameras are used. The joint processing of image sequences of a multi-camera system is a scientific and technical challenge. The processing is divided traditionally into camera calibration, object detection, tracking and interpretation. The fusion of information from different cameras is carried out in the world coordinate system. To reduce the network load, a distributed processing concept can be implemented. Object detection and tracking are fundamental image processing tasks for scene evaluation. Situation assessments are based mainly on characteristic local movement patterns (e.g. directions and speed), from which trajectories are derived. It is possible to recognize atypical movement patterns of each detected object by comparing local properties of the trajectories. Interaction of different objects can also be predicted with an additional classification algorithm. This presentation discusses trajectory based recognition algorithms for atypical event detection in multi object scenes to obtain area based types of information (e.g. maps of speed patterns, trajectory curvatures or erratic movements) and shows that two-dimensional areal data analysis of moving objects with multiple cameras offers new possibilities for situational analysis. © 2012 Springer-Verlag.

关键词： Trajectories

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Automatic seed placement for breast lesion segmentation on US images

Automatic seed placement for breast lesion segmentation on U...

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11th International Workshop on Breast Imaging, IWDM 2012

作者： Massich, Joan Meriaudeau, Fabrice Sentís, Melcior Ganau, Sergi Pérez, Elsa Martí, Robert Oliver, Arnau Martí, Joan Computer Vision and Robotics Group University of Girona Spain Laboratoire Le2i-UMR CNRS University of Burgundy Le Creusot France Department of Breast and Gynecological Radiology UDIAT-Diagnostic Center Parc Taulí Corporation Sabadell Spain Department of Radiology Hospital Josep Trueta of Girona Spain

ISBN: (纸本)9783642312700

Breast lesion boundaries have been mostly extracted by using conventional approaches as a previous step in the development of computer-aided diagnosis systems. Among these, region growing is a frequently used segmentation method. To make the segmentation completely automatic, most of the region growing methods incorporate automatic selection of the seed points. This paper proposes a new automatic seed placement algorithm for breast lesion segmentation on ultrasound images by means of assigning the probability of belonging to a lesion for every pixel depending on intensity, texture and geometrical constraints. The proposal has been evaluated using a set of sonographic breast images with accompanying expert-provided ground truth, and successfully compared to other existing algorithms. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： computer aided diagnosis

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Rapid shallow coastal coral reef mapping using the teardrop system

Rapid shallow coastal coral reef mapping using the teardrop ...

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OCEANS

作者： Francis James Corpuz Prospero Naval Eusebio Capili Jaylord Jauod Roel John Judilla Maricor Soriano Computer Vision and Machine University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Mapua Institute of Technology Manila Philippines Vision and Image Processing Group University of the Philippines Diliman Quezon City Philippines

We present a rapid shallow coastal reef mapping system using a previously developed inexpensive diver less video capture system coupled with a fast-image mosaicking technique, using an affordable GPS logging device. The system replaces the traditional manta tow system of assessing and monitoring large areas of coastal coral reefs and at the same time provides historical visual record for future references. The system utilizes Teardrop, a hollow, teardrop-shaped that houses a commercial underwater point-and-shoot camera. The camera is set to video mode and captures video of the reef while the Teardrop is being towed by a wooden fishing boat. The resulting video is parsed into frames and mosaicked by using fast image labeling. The approximate location of the mosaicked images is recorded by using an inexpensive GPS logger. The coordinates are embedded on the mosaicked images and overlaid on mapping software such as Google Earth for visual record and spatial information integration. The same points are used to compute for the total distance covered by the capturing process. The whole process from coral reef video capture to mosaicking the images and finally embedding the mosaics in mapping software can be done in as short as 1 day, providing coastal managers and local government units with a tool to rapidly visualize and monitor shallow coral reefs.

关键词： Global Positioning System Monitoring Cameras Sea measurements Earth Boats Google

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Camera calibration using two or three vanishing points

Camera calibration using two or three vanishing points

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Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Radu Orghidan Joaquim Salvi Mihaela Gordan Bogdan Orza Center for Multimedia Technologies and Distance Education Technical University of Cluj Napoca Cluj-Napoca Romania Computer Vision and Robotics Group Polytechnic School University of Girona Girona Spain

The perspective projection models the way a 3D scene is transformed into a 2D image, usually through a camera or an eye. In a projective transformation, parallel lines intersect in a point called vanishing point. This paper presents in detail two calibration methods that exploit the properties of vanishing points. The aim of the paper is to offer a practical tool for the choice of the appropriate calibration method depending on the application and on the initial conditions. The methods, using two respectively three vanishing points, are presented in detail and are compared. First, the two models are analyzed using synthetic data. Finally, each method is tested in a real configuration and the results show the quality of the calibration.

关键词： Cameras Calibration Mathematical model Vectors Equations Image segmentation Noise

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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

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.

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

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Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Ioannis Kostavelis Lazaros Nalpantidis Antonios Gasteratos Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Computer Vision and Active Perception Laboratory Centre for Autonomous Systems Royal Institute of Technology Stockholm Sweden

关键词： Correlation Quantization Vectors Accuracy Support vector machines Object recognition Humans

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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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Learning the terrain and planning a collision-free trajectory for indoor post-disaster environments

Learning the terrain and planning a collision-free trajector...

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IEEE International Workshop on Safety, Security, and Rescue robotics (SSRR)

作者： Ioannis Kostavelis Antonios Gasteratos Evangelos Boukas Lazaros Nalpantidis Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Laboratory of Computer Vision and Machine Intelligence Department of Mechanical and Manufacturing Engineering Aalborg University Copenhagen Copenhagen Denmark

Mobile robots dedicated in post-disaster missions should be capable of moving arbitrarily in unknown cluttered environments so as to accomplish their assigned security task. The paper in hand describes such an agent equipped with collision risk assessment capabilities, while it is able to trace an obstacle-free path in the scene as well. The robot exploits machine learning techniques for the traversability evaluation of the environment by making use of geometrical features, which derive from a postprocessing step of the depth map, obtained by an RGBD sensor. Then, the traversable scenes, are assessed by the likelihood the robot to collide on any arbitrary direction in front of it. Besides, the collision risk likelihood is combined with a path tracing algorithm based on Cellular Automata so that an obstacle-free route is then detected. The proposed method has been examined for several indoor scenarios revealing remarkable efficiency.

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Fourier-based Registrations for Two-Dimensional Forward-Looking Sonar Image Mosaicing

Fourier-based Registrations for Two-Dimensional Forward-Look...

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IEEE/RSJ International Conference on Intelligent robotics and Systems

作者： Natalia Hurtós Xavier Cuf Yvan Petillot Joaquim Salvi Computer Vision and Robotics Group (VICOROB) University de Girona 17071 Girona Spain Ocean Systems Laboratory Heriot-Watt University EH14 4AS Edinburgh U.K.

ISBN: (纸本)9781467317375

This paper presents a method to build large-scale mosaics adapted to underwater sonar imagery. By assuming a simplified imaging model, we propose to address the registrations between images using Fourier-based methods which, unlike feature-based methods, prove well suited to handle the characteristics of forward-looking sonar images, such as low resolution, noise, occlusions and moving shadows. The registration between spatially and temporally distant images resulting from loop-closing situations or registrations in featureless areas are feasible, overcoming the main difficulties of feature-based methods. The problem is cast as a pose-based graph optimization, taking into account the uncertainties of the pairwise registrations and being able to incorporate navigation information. After the optimization, a consistent mosaic from different tracklines is generated with increased resolution and higher signal-to-noise ratio than the original images, while the vehicle motion in x,y and heading is also estimated.

关键词： Mosaicing higher heading

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