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

共 373 条记录，以下是221-230 订阅

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Discrete and Continuous Curvature Computation for Real Data

Discrete and Continuous Curvature Computation for Real Data

引用

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

作者： Colbry, Dirk Shrikhande, Neelima Michigan State Univ E Lansing MI 48824 USA Cent Michigan Univ Mt Pleasant MI 48858 USA

ISBN: (纸本)9780819499424

This paper describes two methods for estimating the minimum and maximum curvatures for a 3D surface and compares the computational efficiency of these approaches on 3D sensor data. The classical method of Least Square Fitting (LSF) finds an approximation of a cubic polynomial fit for the local surface around the point of interest P and uses the coefficients to compute curvatures. The Discrete Differential Geometry (DDG) algorithm approximates a triangulation of the surface around P and calculates the angle deficit at P as an estimate of the curvatures. The accuracy and speed of both algorithms are compared by applying them to synthetic and real data sets with sampling neighborhoods of varying sizes. Our results indicate that the LSF and DDG methods produce comparable results for curvature estimations but the DDG method performs two orders of magnitude faster, on average. However, the DDG algorithm is more susceptible to noise because it does not smooth the data as well as the LSF method. In applications where it is not necessary for the curvatures to be precise (such as estimating anchor point locations for face recognition) the DDG method yields similar results to the LSF method while performing much more efficiently.

关键词： 3D scanning Strontium Optical spheres Statistical analysis Facial recognition systems computer graphics Detection and tracking algorithms Evolutionary algorithms Image processing 3D modeling

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Quality control in tile production

Quality control in tile production

引用

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

作者： Kalviainen, H Kukkonen, S Hyvarinen, T Parkkinen, J Lappeenranta Univ Technol Dept Informat Technol FIN-53851 Lappeenranta Finland

ISBN: (纸本)081942983X

This work studies visual quality control in ceramics industry. In tile manufacturing, it is important that in each set of tiles, every single tile looks similar. For example, the tiles should have similar color and texture. Our goal is to design a machine vision system that can estimate the sufficient similarity or same appearance to the human eye. Currently, the estimation is usually done by human vision. Differing from other approaches our aim is to use accurate spectral representation of color, and we are comparing spectral features to the RGB color features. A laboratory system for color measurements is built. Experimentations with five classes of brown tiles are presented. We use chromaticity RGB features and several spectral features for classification with the k-NN classifier and with a neural network, called Self-Organizing Map (SOM). Wt: can classify many of the tiles but there are several problems that need further investigations: larger training and test sets are needed, illuminations effects must be studied further, and more suitable spectral features are needed with more sophisticated classifiers. It is also interesting to develop further the neural approach.

关键词： tiles ceramic industry quality control inspection classification color image processing multispectral images machine vision neural network

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Humans, animals, robots: Handling volumic data flows

Humans, animals, robots: Handling volumic data flows

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

作者： Petrov, V FHU Lab Tech Opt & Laser Technol Ulm Germany

ISBN: (纸本)0819434302

Human visual system is properly suited for reliable and adequate volumic perception of natural environment. Volumic data flows coming from the outer physical space are easily acquired, transferred and processed by eye-brain system in real time. This relates also to the animals which use different complicated mechanisms of optical volumic data acquisition and can navigate safely at high speeds. Un the contrary machine vision systems utilizing currently the stereoscopic effect in attempt to achieve volumic data presentation are very slow, bulky and in a way inelegantly devised. The stereoscopy itself seems can hardly organize the adequate, real time volumic robot vision. Novel general principles of volumic vision were formulated recently by this author. They can be applied also to machines and used in the future rapidly navigating mobile robots. Volumic approach to vision seems much more logical for handling of volumic data flows. Along the lines of this approach and unified concept of volumic imaging it is quite natural to assume fine stratification in depth both for biological volumic data sensors and the necessity of fine stratification in depth for artificial ones. Volumic data sensors in robotics seem must be organized as finely stratified in depth structures. Finely stratified in depth volumic data sensor operating in real time might incorporate volumic gratings and use a special software to interpret the arriving volumic data flow. While the task is very difficult, success would permit to organize volumic robot vision in a different war and to create principally novel type of robotic system, ie, 'one-eyed robots'. Preliminary experiments were performed in this work. Complicated holographic gratings were obtained which might serve as components of a future volumic data sensor. Microphotographs of such gratings taken as horizontally stratified slices are presented.

关键词： human and animal vision volumic vision volumic imaging unified concept of volumic imaging stratified in depth spaces physical and hypothetical volumic spaces and their adequate presentation volumic robot vision robot-bio vision

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Method and Application of Active Visual Tracking Based on Illumination Invariants

Method and Application of Active Visual Tracking Based on Il...

引用

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

作者： Su Jiea Yin Gui-sheng Wang Lei Sun Yong-qian Liu Zheng Harbin Univ Sci & Technol 52 Xuefu Rd Harbin 150080 Peoples R China Harbin Engn Univ Harbin 150001 Peoples R China

ISBN: (纸本)9780819494351

With the development of the application of visual tracking technology, the performance of visual tracking algorithm is important. Due to many kinds of voice, robust of tracking algorithm is bad. To improve identification rate and track rate for quickly moving target, expand tracking scope and lower sensitivity to illumination varying, an active visual tracking system based on illumination invariants is proposed. Camera motion pre-control method based on particle filter pre-location is used to improve activity and accuracy of track for quickly moving target by forecasting target position and control camera joints of Tilt, Pan and zoom. Pre-location method using particle sample filter according to illumination invariants of target is used to reduce the affect of varying illumination during tracking moving target and to improve algorithm robust. Experiments in intelligent space show that the robust to illumination vary is improved and the accuracy is improved by actively adjust PTZ parameters.

关键词： computer visual Active Tracking Particle Filter Model Illumination Invariants Robust

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Dynamic template size control in digital image correlation based strain measurements

Dynamic template size control in digital image correlation b...

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

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

ISBN: (纸本)9780819469243

Image matching is a common procedure in computer vision. Usually the size of the image template is fixed. If the matching is done repeatedly, as e.g. in stereo vision, object tracking, and strain measurements, it is beneficial, in terms of computational cost, to use as small templates as possible. On the other hand larger templates usually give more reliable matches, unless e.g. projective distortions become too great. If the template size is controlled locally dynamically, both computational efficiency and reliability can be achieved simultaneously. Adaptive template size requires though that a larger template can be sampled anytime. This paper introduces a method to adaptively control the template size in a digital image correlation based strain measurement algorithm. The control inputs are measures of confidence of match. Some new measures are proposed in this paper, and the ones found in the literature are reviewed. The measures of confidence are tested and compared with each other as well as with a reference method using templates of fixed size. The comparison is done with respect to computational complexity and accuracy of the algorithm. Due to complex inter-actions of the free parameters of the algorithm, random search is used to find an optimal parameter combination to attain a more reliable comparison. The results show that with some confidence measures the dynamic scheme outperforms the static reference method. However, in order to benefit from the dynamic scheme, optimization of the parameters is needed.

关键词： adaptivity machine vision optimization pattern matching tensile testing

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Lane identification and path planning for autonomous mobile robots

Lane identification and path planning for autonomous mobile ...

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

作者： McKeon, Robert T. Paulik, Mark Krishnan, Mohan Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

ISBN: (纸本)0819464821

This work has been performed in conjunction with the University of Detroit Mercy's (UDM) ECE Department autonomous vehicle entry in the 2006 intelligent Ground Vehicle Competition (***. The IGVC challenges engineering students to design autonomous vehicles and compete in a variety of unmanned mobility competitions. The course to be traversed in the competition consists of a lane demarcated by painted lines on grass with the possibility of one of the two lines being deliberately left out over segments of the course. The course also consists of other challenging artifacts such as sandpits, ramps, potholes, and colored tarps that alter the color composition of scenes, and obstacles set up using orange and white construction barrels. This paper describes a composite lane edge detection approach that uses three algorithms to implement noise filters enabling increased removal of noise prior to the application of image thresholding. The first algorithm uses a row-adaptive statistical filter to establish an intensity floor followed by a global threshold based on a reverse cumulative intensity histogram and a priori knowledge about lane thickness and separation. The second method first improves the contrast of the image by implementing an arithmetic combination of the blue plane (RGB format) and a modified saturation plane (HSI format). A global threshold is then applied based on the mean of the intensity image and a user-defined offset. The third method applies the horizontal component of the Sobel mask to a modified gray scale of the image, followed by a thresholding method similar to the one used in the second method. The Hough transform is applied to each of the resulting binary images to select the most probable line candidates. Finally, a heuristics-based confidence interval is determined, and the results sent on to a separate fuzzy polar-based navigation algorithm, which fuses the image data with that produced by a laser scanner (for obstacle detection).

关键词： image processing image filtering thresholding path planning autonomous navigation

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Self-localization for an Autonomous Mobile Robot Based on an Omni-directional vision System

Self-localization for an Autonomous Mobile Robot Based on an...

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

作者： Chiang, Shu-Yin Lin, Kuang-Yu Chia, Tsorng-Lin Ming Chuan Univ Dept Informat & Telecommun Engn Taoyuan 333 Taiwan Ming Chuan Univ Dept Comp & Commun Engn Taoyuan 333 Taiwan

ISBN: (纸本)9780819499424

In this study, we designed an autonomous mobile robot based on the rules of the Federation of International Robot-soccer Association (FIRA) RoboSot category, integrating the techniques of computer vision, real-time image processing, dynamic target tracking, wireless communication, self-localization, motion control, path planning, and control strategy to achieve the contest goal. The self-localization scheme of the mobile robot is based on the algorithms featured in the images from its omni-directional vision system. In previous works, we used the image colors of the field goals as reference points, combining either dual-circle or trilateration positioning of the reference points to achieve self-localization of the autonomous mobile robot. However, because the image of the game field is easily affected by ambient light, positioning systems exclusively based on color model algorithms cause errors. To reduce environmental effects and achieve the self-localization of the robot, the proposed algorithm is applied in assessing the corners of field lines by using an omni-directional vision system. Particularly in the mid-size league of the RobotCup soccer competition, self-localization algorithms based on extracting white lines from the soccer field have become increasingly popular. Moreover, white lines are less influenced by light than are the color model of the goals. Therefore, we propose an algorithm that transforms the omni-directional image into an unwrapped transformed image, enhancing the extraction features. The process is described as follows: First, radical scan-lines were used to process omni-directional images, reducing the computational load and improving system efficiency. The lines were radically arranged around the center of the omni-directional camera image, resulting in a shorter computational time compared with the traditional Cartesian coordinate system. However, the omni-directional image is a distorted image, which makes it difficult to recognize the

关键词： mobile robot self-localization omni-directional vision dual circle trilateration cross ratio.

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Modeling of radial asymmetry in lens distortion facilitated by modern optimization techniques

Modeling of radial asymmetry in lens distortion facilitated ...

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

作者： de Villiers, Jason P. Leuschner, F. Wilhelm Geldenhuys, Ronelle CSIR Meiring Naude Rd Pretoria South Africa Univ Pretoria Dept Elect Elect & Comp Engn Pretoria South Africa

ISBN: (纸本)9780819479327

Most current lens distortion models use only a few terms of Brown's model, which assumes that the radial distortion is dependant only on the distance from the distortion centre, and an additive tangential distortion can be used to correct lens de-centering. This paper shows that the characterization of lens distortion can be improved by over 79% compared to prevailing methods. This is achieved by using modern numerical optimization techniques such as the Leapfrog algorithm, and sensitivity-normalized parameter scaling to reliably and repeatably determine more terms for Brown's model. An additional novel feature introduced in this paper is to allow the distortion to vary not only with polar distance but with the angle too. Two models for radially asymmetrical distortion (i.e. distortion that is dependant on both polar angle and distance) are discussed, implemented and contrasted to results obtained when no asymmetry is modelled. A sample of 32 cameras exhibiting extreme barrel distortion (due to their 6.0mm focal lengths) is used to show that these new techniques can straighten lines to within 7 hundredths of a pixel RMS over the entire image.

关键词： Asymmetry numerical optimization distortion characterization real-time

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An intelligent Hybrid Behavior Coordination System for an Autonomous Mobile Robot

An Intelligent Hybrid Behavior Coordination System for an Au...

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

作者： Luo, Chaomin Krishnan, Mohan Paulik, Mark Fallouh, Samer Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

ISBN: (纸本)9780819499424

In this paper, development of a low-cost PID controller with an intelligent behavior coordination system for an autonomous mobile robot is described that is equipped with IR sensors, ultrasonic sensors, regulator, and RC filters on the robot platform based on HCS12 microcontroller and embedded systems. A novel hybrid PID controller and behavior coordination system is developed for wall-following navigation and obstacle avoidance of an autonomous mobile robot. Adaptive control used in this robot is a hybrid PID algorithm associated with template and behavior coordination models. Software development contains motor control, behavior coordination intelligent system and sensor fusion. In addition, the module-based programming technique is adopted to improve the efficiency of integrating the hybrid PID and template as well as behavior coordination model algorithms. The hybrid model is developed to synthesize PID control algorithms, template and behavior coordination technique for wall-following navigation with obstacle avoidance systems. The motor control, obstacle avoidance, and wall-following navigation algorithms are developed to propel and steer the autonomous mobile robot. Experiments validate how this PID controller and behavior coordination system directs an autonomous mobile robot to perform wall-following navigation with obstacle avoidance. Hardware configuration and module-based technique are described in this paper. Experimental results demonstrate that the robot is successfully capable of being guided by the hybrid PID controller and behavior coordination system for wall-following navigation with obstacle avoidance.

关键词： Behavior coordination system PID controller wall-following navigation obstacle avoidance template-based navigation autonomous mobile robot module-based programming technique

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Symbolic processing methods for 3D visual processing

Symbolic processing methods for 3D visual processing

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

作者： Tedder, M Hall, EL Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)081944300X

The purpose of this paper is to describe a theory that defines an open method for solving 3D visual data processing and artificial intelligence problems that is independent of hardware or software implementation. The goal of the theory is to generalize and abstract the process of 3D visual processing so that the method can be applied to a wide variety of 3D visual processing problems. Once the theory is described a heuristic derivation is given. Symbolic processing methods can be generalized into an abstract model composed of eight basic components. The symbolic processing model components are: input data;input data interface;symbolic data library;symbolic data environment space;relationship matrix;symbolic logic driver;output data interface and output data. An obstacle detection and avoidance experiment was constructed to demonstrate the symbolic processing method. The results of the robot obstacle avoidance experiment demonstrated that the mobile robot could successfully navigate the obstacle course using symbolic processing methods for the control software. The significance of the symbolic processing approach is that the method arrived at a solution by using a more formal quantifiable process. Some of the practical applications for this theory are: 3D object recognition, obstacle avoidance, and intelligent robot control.

关键词： symbolic processing computer vision laser scanning mobile robots artificial intelligence

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