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检索条件"任意字段=Conference on Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques"

共 375 条记录，以下是121-130 订阅

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REAL-TIME MODEL-BASED vision FOR INDUSTRIAL DOMAINS 12

REAL-TIME MODEL-BASED VISION FOR INDUSTRIAL DOMAINS

引用

12th conference on intelligent robots and computer vision: algorithms and techniques

作者： SEIDA, S MAGEE, M SW RES INST DIV AUTOMAT & DATA SYST 05SAN ANTONIOTX 78228

ISBN: (纸本)0819413208

This paper describes a model based vision system that has been developed which is able to perform model based reasoning at real-time (or near real-time) rates and for which both the hardware and prototyping costs are low. The basic approach taken is to extract a set of useful features from observed models using a library of feature primitive operators. Scale and orientation invariant combinations of these features are used as indices into a hardware lookup table to establish initial correspondence between similar combinations that will be encountered when examining unknown objects. When performing initial recognition of an unknown object, evidence for an object in a particular spatial pose is accumulated, giving rise to an initial set of hypotheses. The strongest hypotheses are then refined by iteratively hypothesizing new (previously uninstantiated) model/object feature matches and computing a confidence measure associated with the current instantiation set. If confidence increases the newly hypothesized instantiation is retained, otherwise it is discarded.

关键词： Visual process modeling Feature extraction Systems modeling computer vision technology Machine vision Computing systems Image processing Robot vision robots 3D modeling

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PROGRESS IN HIGH-LEVEL EXPLORATORY vision 12

PROGRESS IN HIGH-LEVEL EXPLORATORY VISION

引用

12th conference on intelligent robots and computer vision: algorithms and techniques

作者： BRAND, M NORTHWESTERN UNIV INST LEARNING SCIEVANSTONIL 60201

ISBN: (纸本)0819413208

We have been exploring the hypothesis that vision is an explanatory process, in which causal and functional reasoning about potential motion plays an intimate role in mediating the activity of low-level visual processes. In particular, we have explored two of the consequences of this view for the construction of purposeful vision systems: Causal and design knowledge can be used to (1) drive focus of attention, and (2) choose between ambiguous image interpretations. An important result of visual understanding is an explanation of the scene's causal structure: How action is originated, constrained, and prevented, and what will happen in the immediate future. In everyday visual experience, most action takes the form of motion, and most causal analysis takes the form of dynamical analysis. This is even true of static scenes, where much of a scene's interest lies in how possible motions are arrested. This paper describes our progress in developing domain theories and visual processes for the understanding of various kinds of structured scenes, including structures built out of children's constructive toys and simple mechanical devices.

关键词： Visualization Visual analytics Buildings robots computer vision technology Machine vision Motion analysis Pathology Robot vision Visual process modeling

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Matching shape descriptions of objects

Matching shape descriptions of objects

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Shrikhande, N Kulkarni, M Cent Michigan Univ Dept Comp Sci Mt Pleasant MI 48859 USA

ISBN: (纸本)081944300X

A model of an object is an image consisting of features of die object. The input is a gray scale image from which features are computed. In his doctoral thesis [7] J. L. Chen used a model based approach for object recognition. His method is based on Rosin's work [26] for extraction of parts. Both model and scene features are contour based properties. Properties of each part such as area, compactness, convexity etc. are computed and used to match the scene image to the model. This paper extends the algorithm in several directions. The contours are improved using two passes over the initial input image. The notion of internal part or base of an object is introduced and used to normalize the part areas. Insignificant parts are merged with neighboring parts to provide a better segmentation of the scene. Interpretation trees are used to match scene to object. The algorithm is tested on simple hand drawn images and also images of buildings obtained from architectural databases.

关键词： computer vision object recognition image processing

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intelligent robots and computer vision X: algorithms and techniques

Intelligent Robots and Computer Vision X: Algorithms and Tec...

引用

intelligent robots and computer vision X: algorithms and techniques

ISBN: (纸本)0819407445

The conference materials contain 69 papers grouped into twelve sessions dealing with different topics in computer vision. Pattern recognition;human face recognition algorithms and systems;image processing including feature spaces, edge and contour methods, optical character recognition and morphology;Packaging, materials handling, software and manipulation;fuzzy image processing and image understanding are the main topics covered.

关键词： computer vision

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Micro-assembly cell with dual optical/computer vision control for electrostatic gripping of MEMS

Micro-assembly cell with dual optical/computer vision contro...

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conference on intelligent robots and computer vision XXI

作者： Enikov, ET Clark, S Minkov, L Univ Arizona Dept Aeronaut & Mech Engn Tucson AZ 85721 USA

ISBN: (纸本)081945155X

This paper describes the development of a miniature assembly cell for microsystems. The cell utilizes a transparent electrostatic gripper all-owing the use of computer vision for part alignment with respect to the gripper. Part to assembly alignment is achieved via optical triangulation using a fiber-coupled laser and a position sensitive detector (PSD). The system layout, principle of operation and design are described along with the visual and optical control algorithms and their implementation. Experimental measurements of the performance of the stage indicate normal and tangential gripping forces in the range of 0.03-2.5 mN and 1.-9. mN respectively. The visual search algorithm limits the feature tracking speed to 111ms /search. The alignment accuracy of the visual and optical proportional position feedback controls were determined to be +/-7 mum and +/-10 mum respectively.

关键词： electrostatic clamp visual servoing disparate sensing modalities optical feedback

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Flexible inline low cost inspection station

Flexible inline low cost inspection station

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27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Sung, Chen-Ko Fraunhofer Inst Informat & Data Proc IITB D-76131 Karlsruhe Germany

ISBN: (纸本)9780819479327

A possibility to reduce the investment costs is an improved functionality of the inspection station in order to awaken investors' interest to buy. A new concept for 2-D and 3-D metric and logical quality monitoring with a more accurate, flexible, economical and efficient inspection station has been developed and tested at IITB. The inspection station uses short- and wide-range sensors, an intelligent grip system and a so-called "sensor magazine" which make the inspection process more flexible. The sensor magazine consists of various sensor ports with various task-specific, interchangeable sensors. With the sensor magazine and the improved measuring methods, the testing periods and therefore the costs in factory can be substantially decreased.

关键词： Multi sensors wide- and short-range sensors intelligent grip system sensor magazine learning-capable evaluation processes flexible inline quality monitoring robot dynamic and automatic path planning

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A modular real-time vision module for humanoid robots

A modular real-time vision module for humanoid robots

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conference on intelligent robots and computer vision XXIX - algorithms and techniques

作者： Trifan, Alina Neves, Antonio J. R. Lau, Nuno Cunha, Bernardo Univ Aveiro IEETA DETI P-3810193 Aveiro Portugal

ISBN: (纸本)9780819489487

Robotic vision is nowadays one of the most challenging branches of robotics. In the case of a humanoid robot, a robust vision system has to provide an accurate representation of the surrounding world and to cope with all the constraints imposed by the hardware architecture and the locomotion of the robot. Usually humanoid robots have low computational capabilities that limit the complexity of the developed algorithms. Moreover, their vision system should perform in real time, therefore a compromise between complexity and processing times has to be found. This paper presents a reliable implementation of a modular vision system for a humanoid robot to be used in color-coded environments. From image acquisition, to camera calibration and object detection, the system that we propose integrates all the functionalities needed for a humanoid robot to accurately perform given tasks in color-coded environments. The main contributions of this paper are the implementation details that allow the use of the vision system in real-time, even with low processing capabilities, the innovative self-calibration algorithm for the most important parameters of the camera and its modularity that allows its use with different robotic platforms. Experimental results have been obtained with a NAO robot produced by Aldebaran, which is currently the robotic platform used in the RoboCup Standard Platform League, as well as with a humanoid build using the Bioloid Expert Kit from Robotis. As practical examples, our vision system can be efficiently used in real time for the detection of the objects of interest for a soccer playing robot (ball, field lines and goals) as well as for navigating through a maze with the help of color-coded clues. In the worst case scenario, all the objects of interest in a soccer game, using a NAO robot, with a single core 500Mhz processor, are detected in less than 30ms. Our vision system also includes an algorithm for self-calibration of the camera parameters as well

关键词： Robotics robotic soccer computer vision object recognition humanoid robots color classification

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Searching strain field parameters by genetic algorithms

Searching strain field parameters by genetic algorithms

引用

conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Koljonen, Janne Mantere, Timo Kanniainen, Olli Alander, Jarmo T. Univ Vaasa Dept Elect Engn & Automat FIN-65101 Vaasa Finland

ISBN: (纸本)9780819469243

This paper studies the applicability of genetic algorithms and imaging to measure deformations. Genetic algorithms are used to search for the strain field parameters of images from a uniaxial tensile test. The non-deformed image is artificially deformed according to the estimated strain field parameters, and the resulting image is compared with the true deformed image. The mean difference of intensities is used as a fitness function. Results are compared with a node-based strain measurement algorithm developed by Koljonen et al. The reference method slightly outperforms the genetic algorithm as for mean difference of intensities. The root-mean-square difference of the displacement fields is less than one pixel. However, with some improvements suggested in this paper the genetic algorithm based method may be worth considering, also in other similar applications: Surface matching instead of individual landmarks can be used in camera calibration and image registration. Search of deformation parameters by genetic algorithms could be applied in pattern recognition tasks e.g. in robotics, object tracking and remote sensing if the objects are subject to deformation. In addition, other transformation parameters could be simultaneously looked for.

关键词： deformation genetic algorithms machine vision search tensile testing

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Research and Development of Ro-Boat - An Autonomous River Cleaning Robot

Research and Development of Ro-Boat - An Autonomous River Cl...

引用

conference on intelligent robots and computer vision XXXI - algorithms and techniques

作者： Sinha, Aakash Bhardwaj, Prashant Vaibhav, Bipul Mohammad, Noor Omnipresent Robot Technologies Pvt. Ltd. (India) Manav Rachna College Of Engineering (India) Indian Institute Of Technology Guwahati (India) National Institute Of Technology Warangal (India)

ISBN: (纸本)9780819499424

Ro-Boat is an autonomous river cleaning intelligent robot incorporating mechanical design and computer vision algorithm to achieve autonomous river cleaning and provide a sustainable environment. Ro-boat is designed in a modular fashion with design details such as mechanical structural design, hydrodynamic design and vibrational analysis. It is incorporated with a stable mechanical system with air and water propulsion, robotic arms and solar energy source and it is proceed to become autonomous by using computer vision. Both "HSV Color Space" and "SURF" are proposed to use for measurements in Kalman Filter resulting in extremely robust pollutant tracking. The system has been tested with successful results in the Yamuna River in New Delhi. We foresee that a system of Ro-boats working autonomously 24x7 can clean a major river in a city on about six months time, which is unmatched by alternative methods of river cleaning.

关键词： Autonomous robot River cleaning computer vision Multiple object tracking HSV color space SURF Kalman filter

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Navigation using self-initialising active contours.

Navigation using self-initialising active contours.

引用

conference on intelligent robots and computer vision XVI - algorithms, techniques, Active vision, and Materials Handling

作者： Molloy, D Whelan, PF Vision Systems Laboratory School of Electronic Engineering Dublin City University Glasnevin Dublin 9 Ireland

ISBN: (纸本)0819426407

This paper examines a novel approach for extracting motion information to allow the autonomous navigation of an intelligent mobile robot using computer vision in a moving camera, moving object environment. The approach begins by extracting low-level scene feature information using algorithms such as the SUSAN corner and edge detector. A routine is described for converting the information obtained from these stable features to initialisation information for creating active contour models or 'snakes'. Multiple open and closed active contours are identified in an initialisation frame from this primary feature extraction. These contours are allowed to converge more closely to the features to which they are attached. These contours are then allowed to converge to the features within each frame through image sequences, with criteria for the re-initialisation of new contours when motion information in the sequence or a region becomes sparse. The information received from these contour models is then used to determine. the motion information in the scene. Reasons for this approach are outlined and justified. This theoretical approach is then applied to the practical cases of a mobile robot navigating indoor scenes. Large sections of this approach have been implemented in the Khoros environment, with new routines written for this approach. Promising results are already available and this approach is being examined to allow the extraction of depth information in the scene for assisting navigation using a form of '3-D snakes'.

关键词： corners SUSAN active contours snakes edge-linking

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