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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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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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Hierarchical congestion control for robotic swarms

Hierarchical congestion control for robotic swarms

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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Vinicius Graciano Santos Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University Minas Gerais Brazil

Safe and efficient navigation of robotic swarms is an important research problem. One of the main challenges in this area is to avoid congestion, which usually happens when large groups of robots share the same environment. In this paper, we propose the use of hierarchical abstractions in conjunction with simple traffic control rules based on virtual forces to avoid congestion in swarm navigation. We perform simulated and real experiments in order to study the feasibility and effectiveness of the proposed algorithm. Results show that our approach allows the swarm to navigate without congestions in a smooth and coherent fashion, being suitable for large groups of robots.

关键词： Robot kinematics Robot sensing systems Collision avoidance Navigation Force Aerospace electronics

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Retinal vessel tortuosity evaluation via Circular Hough Transform

Retinal vessel tortuosity evaluation via Circular Hough Tran...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Farnoosh Ghadiri HamidReza Pourreza Touka Banaee Morteza Delgir Computer Engineering Department Machine Vision Laboratory Ferdowsi University of Mashhad Iran Computer Engineering Department Machine Vision Laboratory University of Ferdowsi Mashhad Iran Ophthalmic Research Center Khatam-Al-Anbia Hospital Medical science University of Mashhad Iran Computer Science Department Robotics Laboratory Northeastern University USA

Retinal vessel tortuosity has shown to be significantly associated with cardiovascular diseases such as hypertension and diabetes. Despite importance of this field a few techniques have been proposed yet. All previous methods rely on a vessel extraction phase, which its accuracy affects final output and also time consuming. Nobility of presented algorithm is to introduce a method for evaluating retinal vessel tortuosity without any explicit vessel detection. We use the Circular Hough Transform (CHT) based on gradient field of the retinal image. Each vessel curve is detected as a semi-circle by Hough transform and tortuosity of the curve is determined with the help of accumulated value of circle center and its radius. As there are no any specific database for tortuosity evaluation, the algorithm was tasted on database consisting of 40 images, mixture of DRIVE database and images from Khatam-Al-Anbia Hospital consisting of 40 retinal images, of which 20 were tortuous and 20 were non-tortuous. The proposed algorithm can achieve classification rate of 92% along with less computation time in compare of previous methods.

关键词： Transforms Retinal vessels Classification algorithms Biomedical measurements Biomedical imaging Image segmentation

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Selection and recognition of landmarks using terrain spatiograms

Selection and recognition of landmarks using terrain spatiog...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Damian M. Lyons Robotics & Computer Vision Laboratory Computer and Information Science Department Fordham University Bronx NY USA

A team of robots working to explore and map an area may need to share information about landmarks so as to register their local maps and to plan effective exploration strategies. In previous papers we have introduced a combined image and spatial representation for landmarks: terrain spatiograms. We have shown that for manually selected views, terrain spatiograms provide an effective, shared representation for occlusion filtering and for combination of multiple views. In this paper, we present a landmark saliency architecture (LSA) that will automatically select candidate landmarks given some preference settings. Using a dataset of 21 outdoor stereo images generated by LSA, we show that the terrain spatiogram representation reliably recognizes automatically selected landmarks. The terrain spatiogram results are shown to improve on two purely appearance based approaches: template matching and image histogram matching.

关键词： Image color analysis Visualization Robots Histograms Pixel Semantics Humans

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Detection and filtering of landmark occlusions using Terrain Spatiograms

Detection and filtering of landmark occlusions using Terrain...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Damian M. Lyons Robotics & Computer Vision Laboratory Computer and Information Science Department Fordham University Bronx NY USA

A team of robots cooperating to quickly produce a map needs to share landmark information between members so that the local maps can be accurately merged. However, the appearance of landmarks as seen by members of the team can change dramatically due to the phenomenon of occlusion. We have previously presented an approach to landmark representation using Terrain Spatiograms an extension to image spatiograms in which the spatial information relates to the scene rather than the image. Because this representation preserves depth structure, it is possible to identify and filter potential occlusions. We present an approach to identifying and filtering occlusions using terrain spatiograms, and report experimental results on 20 landmark datasets for varying states of occlusion. We show that occlusion can be detected and filtered, resulting in improved landmark matching scores.

关键词： Robots Histograms robotics and automation Matched filters Hazards USA Councils Information filtering Information filters Layout LAN interconnection

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Feasible RRT-based path planning using seventh order Bézier curves

Feasible RRT-based path planning using seventh order Bézier...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Armando A. Neto Douglas G. Macharet Mario F. M. Campos Computer Vision and Robotics Laboratory (Verlab) Computer Science Department Federal University of Minas Gerais Brazil

This paper presents a methodology based on a variation of the Rapidly-exploring Random Trees (RRTs) that generates feasible trajectories for autonomous vehicles with holonomic constraints in environments with obstacles. Our approach is based on seventh order Bézier curves to connect vertexes of the tree, generating paths that do not violate the main kinematic constraints of the vehicle. The methodology also does not require complex kinematic and dynamic models of the vehicle. The smoothness of the acceleration profile of the entire path is directly guaranteed by controlling the curvature values at the extreme points of each Bézier that composes the tree. The proposed algorithm provides fast convergence to the final result with several other advantages, such as the reduction in the number of vertexes of the tree because the method enable connections between vertexes of the tree with unlimited range. In an environment with few obstacles, a very small quantity of vertexes (sometimes only two) is sufficient to take the robot between two points. The properties of the seventh order Bézier formulation are also used to avoid collisions with static obstacles in the environment.

关键词： Vehicles Robots Vehicle dynamics Mathematical model Kinematics Trajectory

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Class-specific grasping of 3D objects from a single 2D image

Class-specific grasping of 3D objects from a single 2D image

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Han-Pang Chiu Huan Liu Leslie Pack Kaelbling Tomás Lozano-Pérez Vision and Robotics Laboratory Sarnoff Corporation Princeton NJ USA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

Our goal is to grasp 3D objects given a single image, by using prior 3D shape models of object classes. The shape models, defined as a collection of oriented primitive shapes centered at fixed 3D positions, can be learned from a few labeled images for each class. The 3D class model can then be used to estimate the 3D shape of a detected object, including occluded parts, from a single image. The estimated 3D shape is used as to select one of the target grasps for the object. We show that our 3D shape estimation is sufficiently accurate for a robot to successfully grasp the object, even in situations where the part to be grasped is not visible in the input image.

关键词： Three dimensional displays Solid modeling Shape Image reconstruction Computational modeling Grasping Training

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Self-organized executive control functions

Self-organized executive control functions

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International Joint Conference on Neural Networks (IJCNN)

作者： Michail Maniadakis Panos Trahanias Jun Tani Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Hellas Crete Greece Laboratory for Behavior and Dynamic Cognition RIKEN Brain Science Institute Wako Saitama Japan

Executive control incorporates cognitive functions involved in the control and management of other cognitive processes. Such high-level skills are hard to be explored with brain imaging studies because they require complex and persistent experimental procedures. Alternatively, computational modeling may provide a new way to indirectly explore executive control mechanisms. The current work adopts this latter approach to explore possible characteristics of executive control, focusing particularly on behavioral rule switching and confidence neurodynamics in artificial agents. To this end, our study explores a robotic version of the classical Wisconsin Card Sorting Test, incorporating also the option of betting. Our ability to perform multiple and statistically independent computational experiments together with the in-depth study of the mechanisms created in the artificial cognitive systems, provides suggestions for the executive control aspects of the human brain.

关键词： Switches Robot sensing systems Brain modeling Neurons Encoding

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Saliency ranking for benthic survey using underwater images

Saliency ranking for benthic survey using underwater images

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International Conference on Control, Automation, robotics and vision (ICARCV)

作者： Matthew Johnson-Roberson Oscar Pizarro Stefan Williams Computational Vision and Active Perception Laboratory School of Computer Science and Communication Royal Institute of Technology Sweden ARC Centre of Excellence of Autonomous Systems Australian Centre of Field Robotics University of Sydney Australia

This paper presents a novel architecture for a classification system based on the visual saliency of images. The work is motivated by the difficulty of reviewing large numbers of images as a human operator in the context of Autonomous Underwater Vehicle (AUV) surveys. We formulate a feature space in which an algorithm operates over color and texture to determine saliency and illustrate how this can be used to find interesting or unusual images within a large data set. The saliency classification based on these general image features allows for overlays highlighting interesting benthos or geologic structures on large scale 3D seafloor reconstructions, quickly providing spatial context to human observers. These results are validated using a set of human trials in which images are classified into salient and non-salient categories by a number of test subjects. The trials show good agreement both between subjects and between the human labels and the automated classification system. The results of the automated technique are also compared directly to a more traditional SVM classification system showing favorable results for our system for generalizing to new environments.

关键词： Pixel Humans Visualization Entropy Image color analysis Indexes Context

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