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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131-140 订阅

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Virtual force field based obstacle avoidance and agent based intelligent mobile robot

Virtual force field based obstacle avoidance and agent based...

引用

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

作者： Sarkar, Saurabh Reynolds, Scott Hall, Ernest Univ Cincinnati Dept Mech Engn 2600 Clifton Ave Cincinnati OH 45221 USA Univ Cincinnati Dept Comp Sci Cincinnati OH 45221 USA

ISBN: (纸本)9780819469243

This paper presents a modified virtual force based obstacle avoidance approach suited for laser range finder. The modified method takes advantage of the polar coordinate based data sent by the laser sensor by mapping the environment in a polar coordinate system. The method also utilizes a Gaussian function based certainty values to detect obstacle. The method successfully navigates through complex obstacles and reaches target GPS waypoints.

关键词： virtual force field laser ranger finder agents

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The 15^th Annual intelligent Ground Vehicle Competition:: intelligent ground robots created by intelligent students

The 15<SUP>th</SUP> Annual Intelligent Ground Vehicle Compet...

引用

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

作者： Theisen, Bernard L. USA Tank Automotive Res Ctr Dev & Engn Warren MI 48397 USA

ISBN: (纸本)9780819469243

The intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 15 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

关键词： intelligent robots autonomous systems ground vehicles engineering education IGVC

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Fruit shape classification using support vector machine

Fruit shape classification using support vector machine

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

作者： Gui, Jiangsheng Rao, Xiuqin Ying, Yibin Zhejiang Sci Tech Univ Dept Elect & Informat Hangzhou 310018 Peoples R China Zhejiang Univ Dept Biosyst Engn & Food Sci Hangzhou 310029 Peoples R China

ISBN: (纸本)9780819469243

A new method along with shape descriptor using support vector machine for classify fruit shape is developed, the image is first subjected to a normalization process using its regular moments to obtain scale and translation invariance, the rotation invariant Zernike features are then extracted from the scale and translation normalized images and the numbers of features are decided by primary component analysis (PCA), at last. these features are input to support vector machine (SVM) classifier and are compared to different classifiers. This method using support vector machine as classifier performs better than traditional approaches that is verified by some experiments.

关键词： machine vision shape classification fruit sorting SVM

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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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Creative learning for intelligent robots

Creative learning for intelligent robots

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

作者： Liao, Xiaoqun Hall, Ernest L. Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)9780819469243

This paper describes a methodology for creative learning that applies to man and machines. Creative learning is a general approach used to solve optimal control problems. The creative controller for intelligent machines integrates a dynamic database and a task control center into the adaptive critic learning model. The task control center can function as a command center to decompose tasks into sub-tasks with different dynamic models and criteria functions, while the dynamic database can act as an information system. To illustrate the theory of creative control, several experimental simulations for robot arm manipulators and mobile wheeled vehicles were included. The simulation results showed that the best performance was obtained by using adaptive critic controller among all other controllers. By changing the paths of the robot arm manipulator in the simulation, it was demonstrated that the learning component of the creative controller was adapted to a new set of criteria. The Bearcat Cub robot was another experimental example used for testing the creative control learning. The significance of this research is to generalize the adaptive control theory in a direction toward highest level of human learning - imagination. In doing this it is hoped to better understand the adaptive learning theory and move forward to develop more human-intelligence-like components and capabilities into the intelligent robot. It is also hoped that a greater understanding of machine learning will motivate similar studies to improve human learning.

关键词： adaptive critic design dynamic programming creative learning Neurocontrol intelligent robots artificial intelligence

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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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New experimental diffractive-optical data on E. Land's Retinex mechanism in human color vision: Part II - art. no. 67640H

New experimental diffractive-optical data on E. Land's Retin...

引用

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

作者： Lauinger, N. Corrsys 3D Sensors AG Wetzlar Germany

ISBN: (纸本)9780819469243

A better understanding of the color constancy mechanism in human color vision [7] can be reached through analyses of photometric data of all illuminants and patches (Mondrians or other visible objects) involved in visual experiments. In Part I [3] and in [4, 5 and 6] the integration in the human eye of the geometrical-optical imaging hardware and the diffractive-optical hardware has been described and illustrated (Fig.1). This combined hardware represents the main topic of the NAMIROS research project (nano- and micro- 3D gratings for optical sensors) [8] promoted and coordinated by Corrsys 3D Sensors AG. The hardware relevant to (photopic) human color vision can be described as a diffractive or interference-optical correlator transforming incident light into diffractive-optical RGB data and relating local RGB onto global RGB data in the near-field behind the 'inverted' human retina. The relative differences at local/global RGB interference-optical contrasts are available to photoreceptors (cones and rods) only after this optical pre-processing.

关键词： RGB color model Color vision Colorimetry Eye Halogens Retina Xenon Visualization Optical correlators Sensors

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Dynamic omni-directional vision localization using a beacon tracker based on particle filter

Dynamic omni-directional vision localization using a beacon ...

引用

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

作者： Cao, Zuoliang Liu, Shiyu Tianjin Univ Technol Tianjin 300191 Peoples R China

ISBN: (纸本)9780819469243

Omni-directional vision navigation for AGVs appears definite significant since its advantage of panoramic sight with a single compact visual scene. This unique guidance technique involves target recognition, vision tracking, object positioning, path programming. An algorithm for omni-vision based global localization which utilizes two overhead features as beacon pattern is proposed in this paper. An approach for geometric restoration of omni-vision images has to be considered since an inherent distortion exists. The mapping between image coordinates and physical space parameters of the targets can be obtained by means of the imaging principle on the fisheye lens. The localization of the robot can be achieved by geometric computation. Dynamic localization employs a beacon tracker to follow the landmarks in real time during the arbitrary movement of the vehicle. The coordinate transformation is devised for path programming based on time sequence images analysis. The beacon recognition and tracking are a key procedure for an onmi-vision guided mobile unit. The conventional image processing such as shape decomposition, description, matching and other usually employed technique are not directly applicable in omni-vision. Particle filter (PF) has been shown to be successful for several nonlinear estimation problems. A beacon tracker based on Particle Filter which offers a probabilistic framework for dynamic state estimation in visual tracking has been developed. We independently use two Particle Filters to track double landmarks but a composite algorithm on multiple objects tracking conducts for vehicle localization. We have implemented the tracking and localization system and demonstrated the relevant of the algorithm.

关键词： omni-directional vision dynamic localization beacon tracker particle filter

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An Adaptive Focal Connectivity Algorithm for Multifocus Fusion

An Adaptive Focal Connectivity Algorithm for Multifocus Fusi...

引用

conference on computer vision and Pattern Recognition (CVPR)

作者： Harishwaran Hariharan Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory University of Tennessee Knoxville TN USA

Multifocus fusion is the process of fusing focal information from a set of input images into one all-in-focus image. Here, a versatile multifocus fusion algorithm is presented for application-independent fusion. A focally connected region is a region or a set of regions in an input image that falls under the depth of field of the imaging system. Such regions are segmented adaptively under the predicate of focal connectivity and fused by partition synthesis. The fused image has information from all focal planes, while maintaining the visual verisimilitude of the scene. In order to validate the fusion performance of our method, we have compared our results with those of tiling and multiscale fusion techniques. In addition to performing a seamless fusion of the focally connected regions, our method out performs the competing methods regarding overall sharpness in all our experiments. Several illustrative examples of multifocus fusion are shown and objective comparisons are provided.

关键词： Layout Image segmentation Focusing Lenses Inspection Microscopy intelligent robots Partitioning algorithms Geometry intelligent systems

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Auditory and visual integration based localization and tracking of humans in daily-life environments

Auditory and visual integration based localization and track...

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2007 IEEE/RSJ International conference on intelligent robots and Systems

作者： Hyun-Don Kim Kazunori Komatani Tetsuya Ogata Hiroshi G. Okuno Speech Media Processing Group Kyoto University Kyoto Japan

The purpose of this research is to develop techniques that enable robots to choose and track a desired person for interaction in daily-life environments. Therefore, localizing multiple moving sounds and human faces is necessary so that robots can locate a desired person. For sound source localization, we used a cross-power spectrum phase analysis (CSP) method and showed that CSP can localize sound sources only using two microphones and does not need impulse response data. An expectation-maximization (EM) algorithm was shown to enable a robot to cope with multiple moving sound sources. For face localization, we developed a method that can reliably detect several faces using the skin color classification obtained by using the EM algorithm. To deal with a change in color state according to illumination condition and various skin colors, the robot can obtain new skin color features of faces detected by OpenCV, an open vision library, for detecting human faces. Finally, we developed a probability based method to integrate auditory and visual information and to produce a reliable tracking path in real time. Furthermore, the developed system chose and tracked people while dealing with various background noises that are considered loud, even in the daily-life environments.

关键词： Humans Face detection Skin Change detection algorithms Microphones Lighting Robot vision systems computer vision Libraries Background noise

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