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

共 409 条记录，以下是61-70 订阅

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Biomimetic sensory abstraction using hierarchical quilted self-organizing maps

Biomimetic sensory abstraction using hierarchical quilted se...

引用

conference on intelligent robots and computer vision xxIV - algorithms, techniques, and active vision

作者： Miller, Jeffrey W. Lommel, Peter H. Draper Lab 555 Technol Sq Cambridge MA 02139 USA

ISBN: (纸本)0819464821

We present an approach for abstracting invariant classifications of spatiotemporal patterns presented in a high-dimensionality input stream, and apply an early proof-of-concept to shift and scale invariant shape recognition. A model called Hierarchical Quilted Self-Organizing Map (HQSOM) is developed, using recurrent self-organizing maps (RSOM) arranged in a pyramidal hierarchy, attempting to mimic the parallel/hierarchical pattern of isocortical processing in the brain. The results of experiments are presented in which the algorithm learns to classify multiple shapes, invariant to shift and scale transformations, in a very small (7 x 7 pixel) field of view.

关键词： Self-Organizing Maps (SOM) unsupervised learning pattern recognition cognitive learning image interpretation robot vision computational neuroscience biomimetic

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A new algorithm for fruit shape classification based on level set

A new algorithm for fruit shape classification based on leve...

引用

conference on intelligent robots and computer vision xxIV - algorithms, techniques, and active vision

作者： Gui, Jiangsheng Ying, Yibin Rao, Xiuqin Zhejiang Univ Dept Biosyst Engn & Food Sci 268 Kaixuan St Hangzhou 310029 Peoples R China

ISBN: (纸本)0819464821

In this research, a new algorithm for fruit shape classification was proposed. The level set representations according to signed distance transforms were used, which are a simple, robust, rich and efficient way to represent shapes. Based on these representations, the rigid transform was adopted to align shapes within the same class, and the simplest possible criterion, the sum of square differences was considered. After align procedure, the average shape representations can easily be derived and shape classification was performed by the nearest neighbor method. Promising results were obtained on experiments showing the efficiency and accurate of our algorithm.

关键词： machine vision shape classification fruit sorting level set

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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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Proceedings of SPIE - Intellingent robots and computer vision xxI: algorithms, techniques, and active vision

Proceedings of SPIE - Intellingent Robots and Computer Visio...

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intelligent robots and computer vision xxI: algorithms, techniques, and active vision

The proceedings contains 33 papers from the conference on SPIE - intelligent robots and computer vision xxI: algorithms, techniques, and active vision. The topics discussed include: learning for intelligent mobile robots;remote operation of robotics systems using WLAN- and CORBA-based architecture;autonomous cross-country driving using active vision;Web-based telerobotics system in a virtual reality environment;automatic calibration and neural networks for robot guidance;recursive least squares approach to calculate motion parameters for a moving camera;and effective color representation for image segmentation under nonwhite illumination.

关键词： Robotics

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vision system for fast 3D obstacle detection via stereovision matching.

Vision system for fast 3D obstacle detection via stereovisio...

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conference on intelligent robots and computer vision xx: algorithms, techniques, and active vision

作者： Bouayed, HA Pissaloux, EE Abdallah, SM CNRS Lab Robot Paris F-78140 Velizy Villacoublay France

ISBN: (纸本)081944300X

Image matching is one of the fundamental problems of computer vision. Various approaches exist. They differ essentially by extracted primitives, by the best match search strategy, and by final applications. Feature based dense matching methods use such geometric primitives as raw pixels, edges, interest points, etc. Some of the correlation based matching methods involve a distance calculation, a time consuming operations. Its enhancement adds pixel complex photometric characteristics such as gradient direction, local curvature and luminosity local disparity, what increases the matching time, but they are usually very noisy. The matching method noise dependency and data volume can be reduced when improving the 'interest point' robustness. This paper proposes to add to 'interest point primitive' a set (vector) of simple characteristics (geometric and photometric), which are invariant to geometric plan transforms. A matching method based upon these enriched pixels and accumulation array concept is presented as well. These elements are useful for 3D obstacle detection in the on-going project "intelligent glasses", our final application. The intelligent glasses is a vision system for humanoid robot and for blinds/visually impaired persons under joint development by Rouen University and Robotics Laboratory in Paris.

关键词： Stereo vision

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An embedded vision system for an unmanned four-rotor helicopter

An embedded vision system for an unmanned four-rotor helicop...

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conference on intelligent robots and computer vision xxIV - algorithms, techniques, and active vision

作者： Lillywhite, Kirt Lee, Dah-Jye Tippetts, Beau Fowers, Spencer Dennis, Aaron Nelson, Brent Archibald, James Brigham Young Univ Dept Elect & Comp Engn Robot Vis Lab Provo UT 84602 USA

ISBN: (纸本)0819464821

In this paper an embedded vision system and control module is introduced that is capable of controlling an unmanned four-rotor helicopter and processing live video for various law enforcement, security, military, and civilian applications. The vision system is implemented on a newly designed compact FPGA board (Helios). The Helios board contains a Xilinx Virtex-4 FPGA chip and memory making it capable of implementing real time vision algorithms. A Smooth Automated intelligent Leveling daughter board (SAIL), attached to the Helios board, collects attitude and heading information to be processed in order to control the unmanned helicopter. The SAIL board uses an electrolytic tilt sensor, compass, voltage level converters, and analog to digital converters to perform its operations. While level flight can be maintained, problems stemming from the characteristics of the tilt sensor limits maneuverability of the helicopter. The embedded vision system has proven to give very good results in its performance of a number of realtime robotic vision algorithms.

关键词： field programmable gate arrays (FPGA) robot vision unmanned helicopter attitude control

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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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Study of cooperative algorithm and group behavior in multi-robot

Study of cooperative algorithm and group behavior in multi-r...

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conference on intelligent robots and computer vision xx: algorithms, techniques, and active vision

作者： Hong, SW Park, KS Shin, SW Ahn, DS Pukyong Natl Univ Sch Mech Engn Intelligent Control Lab Nam Gu Pusan 608739 South Korea

ISBN: (纸本)081944300X

In a multi-agent system, the action selection strategy is important for the cooperation and coordination of multi agents. However the overlap of actions selected individually by each robot makes the acquisition of cooperation behaviors less efficient. In addition to that, a complex and dynamic environment makes cooperation even more difficult. So in this paper, we propose a control algorithm which enables each robot to determine the action for the effective cooperation in multi-robot system. We employ a reinforcement learning in order to choose a proper action for each robot in its action subspace. In this paper, robot soccer system is adopted for the multi-robot environment. To play a soccer game, elementary actions such as shooting and passing must be provided. Q-learning, which is one of the popular methods for reinforcement learning, is used to determine what actions to take. Through simulations, the efficiency of own proposed algorithm is verified for the cooperation in multi robot system.

关键词： robot soccer Q-learning cooperation reinforcement learning fuzzy

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Bayesian stereo: 3D vision designed for sensor fusion

Bayesian stereo: 3D vision designed for sensor fusion

引用

conference on intelligent robots and computer vision xxII - algorithms, techniques and active vision

作者： Larson, J Pless, R Washington Univ St Louis MO 63130 USA

ISBN: (纸本)081945561X

Classical stereo algorithms attempt to reconstruct 3D models of a scene by matching points between two images. Finding points that match is an important part of this process, and point matches are most commonly chosen as the minimum of an error function based on color or local texture. Here we motivate a probabilistic approach to this point matching problem, and provide an experimental design for the empirical measurement of the color matching error for corresponding points. We use this prior in a Bayesian scene reconstruction example, and show that we get better 3D reconstruction by not committing to a specific pixel match early in the visual processing. This allows a calibrated stereo camera to be considered as a probabilistic volume sensor --- which allows it to be more easily integrated with scene structure measurements from other kinds of sensors.

关键词： stereo Bayesian probabilistic sensor fusion

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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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