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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301-310 订阅

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A Novel computer vision Algorithm for Enhancing Image Recognition and Classification 6

A Novel Computer Vision Algorithm for Enhancing Image Recogn...

引用

6th IEEE International conference on Power, intelligent Computing and Systems, ICPICS 2024

作者： Zhong, Herun School of Arts and Design Hubei University of Technology Wuhan430000 China

ISBN: (纸本)9798350374315

computer vision focuses on optimizing computers to understand and interpret visual data from photos or movies, while image recognition specializes in detecting and categorizing objects or patterns in photographs. Technological advancements have revolutionized the field of computer science and found applications in various fields such as robotics, healthcare, security, and entertainment. This article offers a comprehensive overview of the novel approaches of computer vision algorithms widely used in enhancing image recognition and classification. The discipline deals with extracting, analyzing, and understanding information from images or videos by developing algorithms that enable robots to see and comprehend visual information similar to humans. Image recognition primarily emphasizes automatic identification and categorization of objects or patterns in pictures. According to findings, significant developments have been made due to large datasets availability along with improvements in deep learning techniques leveraging enhanced processor power. Convolutional neural networks are now the dominant approach for image recognition problems within deep learning field attaining consistently high-performance levels across several benchmarks. © 2024 IEEE.

关键词： Convolutional neural networks

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Some single instruction multiple data algorithms for plane affine transformation calculation

Some single instruction multiple data algorithms for plane a...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Amiot, Franck Pissaloux, Edwige E. Bonnin, Patrick Universite de Rouen Mont Saint Aignan France

This paper addresses a method for implementation of some basic geometric transformation, namely rotation and scale, on 1D parallel SIMD computers. Solutions to solve many implementation details such as 2D image scanning with 1D machine, the floating point arithmetic simulation and an approximation of the transformed pixel spatial co-ordinates are proposed. The proposed approach tolerates up to ±15° rotation and up to ±50% continue scale changes between images. Those transformations can be used for construction of robust matching primitives useful for robot applications. The evaluation of the proposed method, on SYMPATI2, a French 1D parallel computer (designed by CEA,LETI) is reported.

关键词： computer vision

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Designing and Making the Intelligence Assistant Robot and controlling it by the fuzzy procedure

Designing and Making the Intelligence Assistant Robot and co...

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10th International conference on Electronics, computer and Computation (ICECCO)

作者： Zabbah, Iman Foolad, Shima Chaharaqran, Bahram Mazlooman, Reza Islamic Azad Univ Torbat E Heydarieh Branch Dept Comp Tehran Iran Semnan Univ Dept Comp Semnan Iran Maraghen Sanati Univ Dept Comp Maragheh Iran Natl Iranian Oil Prod Distribut Co Torbat Heydarieh Branch Torbat Heydarieh Iran

ISBN: (纸本)9781479933433

Mobile robots are those with the capability of moving in an environment. The controller of these robots needs to have the ability to do intelligent behaviours in an uncertain environment. Today fuzzy control of mobile robots in non-structured environments is increasing. Many represented algorithms for mobile robot navigation don't manifest appropriate performance in dynamic environments. This article aims at designing and making an intelligence robot. This robot is able to detect a specified target and track it. Velocity and steering of this robot is controlled by the fuzzy logic. Robot velocity is adjusted according to its distance from the target. This article is expressed the features of this mobile robot including different mechanical and electronic infrastructures, fuzzy navigation and vision controller. Navigation system of this robot makes its fuzzy decisions only based on the machine vision techniques and unlike many robots, it doesn't depend on sensor. It is concluded that robot with fuzzy navigation have 60% time saving than the non-fuzzy. The results obtained indicate its appropriate performance in order to navigate a target-oriented mobile robot in an undetermined and dynamic environment.

关键词： Mobile robot navigation Machine vision Robot fuzzy control Target tracking Intelligence robot

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Saturation in active vision systems and its effects on tracking performance

Saturation in active vision systems and its effects on track...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Cahn von Seelen, Ulf M. Bajcsy, Ruzena Sensar Inc Moorestown United States

Linear models are a popular tool to characterize the performance of active vision systems. They cannot, however, capture the nonlinear limits of the system performance that arise out of the physical limitations of the real system. We examine how the finite field of view and the limited motor torque impose bounds on the linear operation of an active vision system in a fixation task. We derive the bounds by analyzing a real active vision system and measuring its response to repeatable and controllable target motions generated by a robot arm. The knowledge of the operational bounds can guide us in deciding which aspects of the active vision system to improve for better overall performance.

关键词： computer vision

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Design development of steering and speed control for an intelligent mobile robot

Design development of steering and speed control for an inte...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Kolli, Kalyan Chakravarthi Kola, Krishnamohan Hall, Ernest L. Univ of Cincinnati Cincinnati United States

Exploratory research on the design of a modular autonomous mobile robot controller for steering and speed control is described. The high level control of the robot incorporates a fuzzy logic approach. Steering and speed control are achieved using a three-axis Galil motion controller. The steering mechanism and the speed control involve the parallel control of the robot's two front wheels based on decisions made by the upper level fuzzy logic to guide the robot in a desired direction to follow a specific path and avoid obstacles in that path. The steering motors are Electrocraft brush DC motor. The BDC amplifiers are run in the current loop mode. The overall control is supervised by a personal computer through the multi-axis controller. The system has been simulated on Matlab and Simulink and optimal values for the digital gains were achieved for desired control. Testing of these systems has been done in a laboratory setting as well as on an outside track with positive results.

关键词： Mobile robots

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Comparison of optical modeling and neural networks for robot guidance

Comparison of optical modeling and neural networks for robot...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Parasnis, Sameer Velidandla, Sasanka Hall, Ernest Anand, Sam Univ of Cincinnati Cincinnati United States

A truly autonomous robot must sense its environment and react appropriately. These issues attain greater importance in an outdoor, variable environment. Previous mobile robot perception systems have relied on hand-coded algorithms for processing sensor information. Recent techniques involve the use of artificial neural networks to process sensor data for mobile robot guidance. A comparison of a fuzzy logic control for an AGV and a neural network perception is described in this work. A mobile robot test bed has been constructed using a golf cart base. The test bed has a fuzzy logic controller which uses both vision and obstacle information and provides the steering and speed controls to the robot. A feed-forward neural network is described to guide the robot using vision and range data. Suitable criteria for comparison will be formulated and the hand-coded system compared with a connectionist model. A comparison of the two systems, with performance, efficiency and reliability as the criteria, will be achieved. The significance of this work is that it provides comparative tradeoffs on two important robot guidance methods.

关键词： computer vision

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Wireless video monitoring and robot control in security applications

Wireless video monitoring and robot control in security appl...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Nurkkala, Eero A. Pyssysalo, Tino Roning, Juha Dep of Electrical Engineering Oulu Finland

This research focuses on applications based on wireless monitoring and robot control, utilizing motion image and augmented reality. These applications include remote services and surveillance-related functions such as remote monitoring. A remote service can be, for example, a way to deliver products at a hospital or old people's home. Due to the mobile nature of the system, monitoring at places with privacy concerns is possible. On the other hand, mobility demands wireless communications. Suitable and present technologies for wireless video transfer are weighted. Identification of objects with the help of Radio Frequency Identifying (RFID) technology and facial recognition results in intelligent actions, for example, where the control of a robot does not require extensive workload from the user. In other words, tasks can be partially autonomous. RFID can be also used in augmentation of the video view with virtual objects. As a real-life experiment, a prototype environment is being constructed that consists of a robot equipped with a video camera and wireless links to the network and multimedia computer.

关键词： intelligent robots

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Illuminant-adaptive diffractive-optical RGB-color sensor: 3D grating-optical cross-correlator calculating colored shadows in human vision.

Illuminant-adaptive diffractive-optical RGB-color sensor: 3D...

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conference on intelligent robots and computer vision XXI

作者： Lauinger, N DATRON Sensorsyst GmbH CORRSYS Wetzlar Germany

ISBN: (纸本)081945155X

Colored shadows are observed when two differently colored lights are combined in twilights. When both lights add to an equi-energy white 'balanced' spectrum, the hues of the shadows show regular opponent colors, being reciprocals of the colors of the lights. When a white and a colored light in a twilight add to an 'unbalanced' spectrum, the hues of the shadows result from the same laws of opponency and reciprocity, but the eyes see "what they have optically calculated" instead of seeing "what really (physically) there is". At adaptation to the colored light, unbalanced states in physics become physiologically re-balanced by diffractive-optical chromatic resonance, guaranteeing color constancy at variations of illuminants. Colored shadows can be interpreted as serial products of diffractive 3D :grating-optical von Laue interferences and of optical cross-correlations between local and global information in the human eye. The human eye's hardware, with diffractive-optical multi-layer gratings in aperture and image space, represents an illuminant-adaptive diffractive-optical RGB Color Sensor guaranteeing color space normalization towards RGB equilibrium states (RGB white norms) in reciprocal grating space.

关键词： RGB color model Eye Bismuth Silicon Sun Visible radiation Physics Colorimetry Diffraction Diffraction gratings

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Active object recognition using appearance-based representations derived from solid geometric models

Active object recognition using appearance-based representat...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Sipe, Michael A. Casasent, David Carnegie Mellon Univ Pittsburgh United States

We present new test results for our active object recognition algorithms. The algorithms are used to classify and estimate the pose of objects in different stable rest positions and automatically re-position the camera if the class or pose of an object is ambiguous in a given image. Multiple object views are now used in determining both the final object class and pose estimate;previously, multiple views were used for classification only. A feature space trajectory (FST) in eigenspace is used to represent 3-D distorted views of an object. FSTs are constructed using images rendered from solid models. We discuss lighting and material settings for photorealism in the rendering process. The FSTs are analyzed to determine the camera positions that best resolve ambiguities. Real objects are recognized from intensity images using the FST representation derived from rendered imagery.

关键词： computer vision

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Predictive optical flow algorithm for aircraft detection

Predictive optical flow algorithm for aircraft detection

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： McCandless, Jeffrey W. Ahumada Jr., Albert J. NASA Ames Research Cent Moffett Field United States

A computer vision algorithm was developed to detect moving aircraft located in video images. Using a gradient-based approach, the algorithm computes optical flow vectors in each frame of the sequence. Vectors with similar characteristics (location, magnitude, and direction) are clustered together using a spatial consistency test. Vectors that pass the spatial consistency test are extended temporally to make predictions about the optical flow locations, magnitudes, and directions in subsequent frames. The actual optical flow vectors that are consistent with the predicted vectors are labeled as vectors associated with a moving target. The algorithm was tested on images obtained with a video camera mounted below the nose of a Boeing 737. The algorithm correctly detected an aircraft from a distance of one mile in over 80% of the frames with zero false alarms.

关键词： computer vision

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