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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261-270 订阅

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INFORMED EDGE LINKING USING A DIRECTIONAL POTENTIAL FUNCTION 12

INFORMED EDGE LINKING USING A DIRECTIONAL POTENTIAL FUNCTION

引用

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

作者： RIORDAN, V ZHU, QM UNIV NEBRASKA DIGITAL IMAGING & COMP VIS LABOMAHANE 68182

ISBN: (纸本)0819413208

Low level edge detection operators usually do not generate contiguous edges, leaving objects in images with discontinuous borders. This, coupled with inherent signal noises, makes it difficult to identify objects in images. Here we describe a new algorithm that connects disjoint edge pixels to form continual object boundaries. We model the edge images as potential fields deployed with energies at the edge pixel positions all over the images. Pixels at the edge disjoint positions are charged by the combining forces of these edge pixels in proportion to the relative distances and directions of these pixels. An intrinsic part of the process is the identification of terminal edge pixels (TEP), accompanying with a classification of edge pixels in terms of the pixel connection patterns, to provide critical information for possible connectivity of edge segments. The algorithm applies a potential evaluation function to measure the likelihood of edge linking in certain directions for given TEPs. To reduce the computational overhead and improve the efficiency of the algorithm, an informed search method is used to locate significant edge pixels that present the most strong linking forces to a given TEP. The potential value for the TEP is calculated with respect to the edge directions dominated by the linking forces. When the potential value exceeds a given threshold in a direction, an extension is made at the TEP position in that direction. The process iterates until desired results are attained, using a global edge pattern evaluation scheme.

关键词： Image processing Robot vision Edge detection computer vision technology Machine vision Image analysis Image classification Image segmentation Interference (communication) Object recognition

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A computer vision Algorithm for Path Planning in Mobile robots 22

A Computer Vision Algorithm for Path Planning in Mobile Robo...

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22nd IEEE conference on Pervasive and intelligent Computing

作者： Ruggieri, Claudio Russo, Miriana Santoro, Corrado Santoro, Federico Fausto STMicroelect Syst Res & Applicat I-95121 Catania Italy Univ Catania Dept Math & Informat Catania Italy

ISBN: (纸本)9798331522759;9798331522742

In robotics, route planning is essential to ensure the safe and efficient movement of robots within the workplace. This process involves determining a trajectory, usually a series of points in the workspace, to achieve a specific goal. It is essential to consider criteria such as reducing the length of the route, the number of manoeuvres and the avoidance of obstacles. Route planning techniques generally require modelling the environment, representing both the structure and the obstacles (fixed or mobile), and the implementation of algorithms that generate the trajectory through the free areas of the environment. This approach often includes constructing a graph of possible trajectories and using minimum path search algorithms, such as A*. This article presents a route planning algorithm that uses Voronoi diagrams and uses artificial vision algorithms. In addition, a case study is described in which the proposed technique is applied to guide an automated system through a maze drawn on a whiteboard by a user.

关键词： path planning robotic systems virtual environment voronoi diagrams opencv

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Automatic calibration and neural networks for robot guidance

Automatic calibration and neural networks for robot guidance

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conference on intelligent robots and computer vision XXI

作者： Sethuramasamyraja, B Ghaffari, M Hall, EL Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)081945155X

An autonomous robot must be able to sense its environment and react appropriately in a variable environment. The University of Cincinnati Robot team is actively involved in building a small, unmanned, autonomously guided vehicle for the International Ground Robotics Contest organized by Association for Unmanned Vehicle Systems International (AUVSI) each year. The unmanned vehicle is supposed to follow an obstacle course bounded by two white/yellow lines, which are four inches thick and 10 feet apart. The navigation system for one of the University of Cincinnati's designs, Bearcat, uses 2 CCD cameras and an image-tracking device for the front end processing of the image captured by the cameras. The three dimensional world co-ordinates were reduced to two dimensional image coordinates as a result of the transformations taking place from the ground plane to the image plane. A novel automatic calibration system was designed to transform the image co-ordinates back to world co-ordinates for navigation purposes. The purpose of this paper is to simplify this tedious calibration using an artificial neural network. Image processing is used to automatically detect calibration points. Then a back projection neural algorithm is used to learn the relationships between the image coordinates and three-dimensional coordinates. This transformation is the main focus of this study. Using these algorithms, the robot built with this design is able to track and follow the lines successfully.

关键词： calibration robotics neural network robot guidance robot vision

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Joint probabilistic techniques for tracking objects using multiple visual cues

Joint probabilistic techniques for tracking objects using mu...

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Proceedings of the 1998 IEEE/RSJ International conference on intelligent robots and Systems. Part 1 (of 3)

作者： Rasmussen, Christopher Hager, Gregory D. Yale Univ New Haven United States

robots relying on vision as a primary sensor frequently need to track common objects such as people, cars, and tools in order to successfully perform autonomous navigation or grasping tasks. These objects may comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying characteristics. In this paper, we present a framework for sharing information among disparate state estimation processes operating on the same underlying visual object. Well-known techniques for joint probabilistic data association are adapted to yield increased robustness when multiple trackers attuned to different visual cues are deployed simultaneously. We also formulate a measure of tracker confidence, based on distinctiveness and occlusion probability, which permits the deactivation of trackers before erroneous state estimates adversely affect the ensemble. We will discuss experiments using color-region, and snake-based tracking in tandem that demonstrate the efficacy of this approach.

关键词： computer vision

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Grating optical diffractive image pre-processing in optical sensors copying human vision (OPTORETINA)

Grating optical diffractive image pre-processing in optical ...

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

作者： Lauinger, N CORRSYS GMBH D-35578 Wetzlar Germany

ISBN: (纸本)081942983X

Three-dimensional multilayer phase gratings (nuclear layers in the human retina) of oscillating cells positioned in the image plane of a monocular optical imaging system transform tight double cones by diffraction and pulsation (quantization) into the reciprocal space behind the grating (Fourier-space in the Fresnel-nearfield). This effect we call OPTORETINA not only guarantees the transformation of the physical stimuli parameters (intensity/wavelength) in the visible spectrum into three chromatically tuned adaptive RGB-color channels (diffraction orders with Brightness-Hue-Saturation aspects) and of object. distances in 3D-space into spatial frequencies or temporal phase differences in reciprocal space (the MULTIDIST grating optical sensors developed at CORRSYS). The 3D-grating, acting as a spatiotemporal frequency and spectral filter, contributes to image pre-processing in Fourier-space. it allows patchwise Fourier-analysis in the Fresnel-nearfield based on weighted Patterson maps of centrosymmetric hexagonal multilayer gratings. Spectral/temporal modulation and spatial frequency analysis seem to be orthogonal to each other as in audition. The OPTORETINA with its cellular diffractive 3D-gratings and their power spectra illustrates a specific part of cortical 4D-spatiotemporal processing. A cortical modulator becomes relevant for temporal coincidence detection and spectral/spatiotemporal correlation in complex image processing, relating multimodal stimulus parameters to internal timing.

关键词： OPTORETINA image processing diffractive optical filtering spatiotemporal frequency analysis 3D-gratings Patterson map

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Towards Event-driven Object Detection with Off-the-shelf Deep Learning

Towards Event-driven Object Detection with Off-the-shelf Dee...

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25th IEEE/RSJ International conference on intelligent robots and Systems (IROS)

作者： Iacono, Massimiliano Weber, Stefan Glover, Arren Bartolozzi, Chiara Ist Italiano Tecnol ICub Facil Genoa Italy

ISBN: (纸本)9781538680940

Event cameras are an emerging technology in computer vision, offering extremely low latency and bandwidth, as well as a high temporal resolution and dynamic range. Inherent data compression is achieved as pixel data is only produced by contrast changes at the edges of moving objects. However, current trends in state-of-the-art visual algorithms rely on deep-learning with networks designed to process colour and intensity information contained in dense arrays, but are notoriously computationally heavy. While the combination of these visual technologies could lead to fast, efficient, and accurate detection and recognition algorithms, it is uncertain whether the compressed event-camera data actually contain the required information for these techniques to discriminate between objects and a cluttered background. This paper presents a pilot study in which off-the-shelf deep-learning is applied to visual events for object detection on the iCub robotic platform, and analyses the impact of temporal integration of the event data. We also present a novel pipeline that bootstraps event-based dataset annotation from mature frame-based algorithms, in order to more quickly generate the required datasets.

关键词： Cameras Robot vision systems Visualization Training Object detection

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An Online Visual Loop Closure Detection Method for Indoor Robotic Navigation 32

引用

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

作者： Erhan, Can Sariyanidi, Evangelos Sencan, Onur Temeltas, Hakan Istanbul Tech Univ Control & Automat Engn Dept TR-34469 Istanbul Turkey Ctr Intelligent Sensing London E1 4NS England

ISBN: (纸本)9781628414967

In this paper, we present an enhanced loop closure method* based on image-to-image matching relies on quantized local Zernike moments. In contradistinction to the previous methods, our approach uses additional depth information to extract Zernike moments in local manner. These moments are used to represent holistic shape information inside the image. The moments in complex space that are extracted from both grayscale and depth images are coarsely quantized. In order to find out the similarity between two locations, nearest neighbour (NN) classification algorithm is performed. Exemplary results and the practical implementation case of the method are also given with the data gathered on the testbed using a Kinect. The method is evaluated in three different datasets of different lighting conditions. Additional depth information with the actual image increases the detection rate especially in dark environments. The results are referred as a successful, high-fidelity online method for visual place recognition as well as to close navigation loops, which is a crucial information for the well known simultaneously localization and mapping (SLAM) problem. This technique is also practically applicable because of its low computational complexity, and performing capability in real-time with high loop closing accuracy.

关键词： Loop closure Zernike Moments image processing SLAM depth map indoor navigation

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Scenario-based simulation of intelligent driving functions using neural networks 9

Scenario-based simulation of intelligent driving functions u...

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9th International conference on Computing, Communication and Networking Technologies (ICCCNT)

作者： Kaur, Parampreet Sobti, Rajeev Lovely Profess Univ Sch Comp Sci Engn Jalandhar India

ISBN: (纸本)9781538644300

The modern technological era is witnessing a significant advancement in AI related fields such as machine learning, mobile robots and autonomous vehicles. The success of such systems is immensely dependent on computer vision algorithms. The entirely software enabled intelligent vehicles will soon be hitting the roads in the coming decade. Such self-controlled mobile robots may still be vulnerable to accidents or crashes. Therefore, the industry requires some state of the art techniques to substantiate the safety and protection of its passengers as well as other road users. Simulation based testing methods have been in use from a long time, but the newer smart vehicle innovations require better versions of simulation techniques. We thus provide an improved mechanism for simulation testing to validate safe navigation of cars in variety of traffic scenarios. Neural network approach integrated with agent based modelling is described in this paper.

关键词： Agent based modelling intelligent driving SAE autonomy levels simulation ADAS

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High-speed object matching and localization using gradient orientation features

High-speed object matching and localization using gradient o...

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

作者： Xu, Xinyu van Beek, Peter Feng, Xiaofan Sharp Labs Amer Camas WA 98607 USA

ISBN: (纸本)9780819499424

In many robotics and automation applications, it is often required to detect a given object and determine its pose (position and orientation) from input images with high speed, high robustness to photometric changes, and high pose accuracy. We propose a new object matching method that improves efficiency over existing approaches by decomposing orientation and position estimation into two cascade steps. In the first step, an initial position and orientation is found by matching with Histogram of Oriented Gradients (HOG), reducing orientation search from 2D template matching to 1D correlation matching. In the second step, a more precise orientation and position is computed by matching based on Dominant Orientation Template (DOT), using robust edge orientation features. The cascade combination of the HOG and DOT feature for high-speed and robust object matching is the key novelty of the proposed method. Experimental evaluation was performed with real-world single-object and multi-object inspection datasets, using software implementations on an Atom CPU platform. Our results show that the proposed method achieves significant speed improvement compared to an already accelerated template matching method at comparable accuracy performance.

关键词： Object matching fast object search fast template matching histogram of oriented gradients dominant orientation template coarse to fine search factory inspection machine vision robotics

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The effect of spatial resolution reduction techniques on the temporal properties of video sequences

The effect of spatial resolution reduction techniques on the...

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IEEE/RSJ International conference on intelligent robots and Systems

作者： Saitwal, K Maciejewski, AA Roberts, RG Colorado State Univ Dept Elect & Comp Eng Ft Collins CO 80523 USA

ISBN: (纸本)0780389123

Singular value decomposition (SVD) is a common technique that is performed on video sequences in a number of computer vision and robotics applications. The left singular vectors represent the eigenimages, while the right singular vectors represent the temporal properties of the video sequence. It is obvious that spatial reduction techniques affect the left singular vectors, however, the extent of their effect on the right singular vectors is not clear. Understanding how the right singular vectors are affected is important because many SVD algorithms rely on computing them as an intermediate step to computing the eigenimages. The work presented here quantifies the effects of different spatial resolution reduction techniques on the right singular vectors that are computed from those video sequences. Examples show that using random sampling for spatial resolution reduction rather than a low-pass filtering technique results in less perturbation of the temporal properties.

关键词： singular value decomposition right singular vectors spatial resolution reduction temporal properties

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