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Approach for demonstrating safety for a collision avoidance system

Approach for demonstrating safety for a collision avoidance ...

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international conference on computer Safety, Reliability, and Securitym, SAFECOMP 2015 and held 3rd international Workshop on Assurance Cases for Software-Intensive Systems ASSURE 2015, Workshop on Dependable Embedded and Cyber-Physical Systems and Systems-of-Systems, DECSoS 2015, 2nd international Workshop on the Integration of Safety and Security Engineering, ISSE 2015, Workshop on Reliability and Security Aspects for Critical Infrastructure Protection, ReSA4CI 2015, and 4th internationalWorkshop on NextGeneration of System Assurance Approaches for Safety-Critical Systems SASSUR, 2015

作者： Gruber, Thomas Zinner, Christian AIT Austrian Institute of Technology GmbH Donau-City-Strasse 1 Vienna Austria

ISBN: (纸本)9783319242484

For many years, the Digital Safety and Security Department of the Austrian Institute of Technology has been developing stereo vision algorithms for various application purposes. Recently, these algorithms have been adapted for use in a collision avoidance system for tramways. The safety validation of such a system is a specific challenge as - like in the automotive domain - the rate of false positives cannot be lowered to zero. While automotive suppliers typically tackle with this problem by reducing the sensitivity of the system and validating it in hundreds of thousands of test kilometres, this paper presents an approach how it is possible to demonstrate safety with a carefully chosen functionality and less field test kilometres. © Springer international Publishing Switzerland 2015.

关键词： Stereo image processing

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Fast Artificial Landmark Detection for Indoor Mobile Robots

Fast Artificial Landmark Detection for Indoor Mobile Robots

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3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on computer Science and Information Systems (FedCSIS)

作者： Kartashov, Dmitriy Huletski, Arthur Krinkin, Kirill Acad Univ St Petersburg Russia St Petersburg State Electrotech Univ LETI St Petersburg Russia

ISBN: (纸本)9788360810668

Nowadays the big challenge in simultaneous localization and mapping (SLAM) of mobile robots is the creation of efficient and robust algorithms. Significant Number of SLAM algorithms rely on unique features or or use artificial landmarks received from camera images. Feature points and landmarks extraction from images have two significant drawbacks: CPU consumption and weak robustness depending on environment conditions. In this paper we consider performance issues for landmark detection, introduce a new artificial landmark design and fast algorithm for detecting and tracking them in arbitrary images. Also we provide results of performance optimization for different hardware platforms.

关键词： SLAM (robots) cameras feature extraction mobile robots object detection robot vision SLAM algorithms arbitrary images artificial landmark detection camera images feature points hardware platforms indoor mobile robots landmark extraction performance issues performance optimization simultaneous localization and mapping Cameras Detection algorithms Graphics processing units image color analysis Mobile robots Robustness

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A Real-Time Big Data Architecture for Glasses Detection Using computer vision Techniques

A Real-Time Big Data Architecture for Glasses Detection Usin...

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international conference on Future Internet of Things and Cloud (FiCloud)

作者： Alberto Fernández Rubén Casado Rubén Usamentiaga Fundación CTIC (Technological Center) Technological Scientific Park of Gijón Gijón Asturias Spain University of Oviedo Gijón Asturias Spain

Automatic glasses detection is a hot topic withing the large-scale face images classification domain, which has impact on face recognition or soft biometrics for person identification. In many practical video surveillance applications, the faces acquired by cameras are low resolution. Therefore, this type of applications requires processing of a large number of relatively small-sized images. However, continuous stream of image and video data processing is a big data challenge. This need fits with the goals of Big Data streaming processing systems. In this paper, we propose a real-time Big Data architecture in order to collect, maintain and analyze massive volumes of images related with the problem of automatic glasses detection. This architecture can be used as an automatic image tagging related with glasses detection on face images.

关键词： Big data Streaming media Face Glass Fasteners computer architecture Support vector machines

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Time Optimized Digital image processing of Ball and Plate System Using Artificial Neural Network

Time Optimized Digital Image Processing of Ball and Plate Sy...

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RSI/ISM international conference on Robotics and Mechatronics

作者： Yasaman Parandian Hannaneh Z. Arabshahi Ali Nasr S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. Department of Mechanical Engineering K.N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781467372350

Regarding robot interaction with moving objects and the necessity for robot controller to react in a timely manner having the objects current position, finding an efficient positioning method has always been a challenge. As ball and plate system is considered to be a standard experimental system in control laboratories. The system is consisted of the following pieces: a horizontal plate which gets tilted along each horizontal axes. The ball, which is located on the plate;is controlled by the system in a way to be placed in any point on the plate. In fact, the ball and plate system is an extension of the classical ball on beam experiment that is often used to study various types of control and stability problems.

关键词： Forward Kinematics Neural Networks Real-Time computer vision 3RRS Parallel Robot Ball and Plate

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A novel probabilistic approach of colored object detection and design of a gesture based real-time mouse tracking along with virtual teaching intended for color-blind people

A novel probabilistic approach of colored object detection a...

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international conference on Signal processing and Integrated Networks (SPIN)

作者： Abhinaba Bhattacharjee Indrani Jana Ankana Das Debasish Kundu Sudipta Ghosh Sauvik Das Gupta Department of Electronics and Communication Engineering Adamas Institute of Technology Kolkata Netaji Subhash Engineering College Kolkata West Bengal University of Technology Kolkata West Bengal India Bengal Institute of Technology and Management Birbhum West Bengal India School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

The study of logic led directly to the invention of the programmable digital electronic computer. The theory of computation inspired us to consider the possibility of building an electronically intelligent brain leading to artificial intelligence. We have seen the 3rd generation smart phones and laptops with LED display having both resistive and capacitive touch technology. This paper presents a conceptual approach of controlling mouse movements, writing texts and sketching colored - images by simply making real time gestures in air with colored objects or colored finger caps without making any physical surface contact unlike the (Touch Technology). With the help of the artificial Digital vision we integrate image processing along with Gesture Recognition to generate a Graphical User Interface in order to acquire physical aerial gestures and plot 2-Dimensional curves onto the computer screen using a real time camera (computer webcam). The graphics or texts so generated on screen can be projected to a wall using a projector in a classroom which especially assists the `lecturers with paralysed legs-who cannot write on a blackboard' or `lecturers suffering from color - blindness or amblyopia'.

关键词： image color analysis Mice Webcams Mathematical model Color computers Real-time systems

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Analysis of a New paradigm for Depth vision Application in Augmented HCI 3

Analysis of a New paradigm for Depth Vision Application in A...

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3rd international conference on Communications and Signal processing (ICCSP)

作者： Sinha, Subarna Deb, Suman Deb, Subhrajyoti Biswas, Bhaskar Natl Inst Technol Agartala Dept Comp Sci & Engn Agartala India

ISBN: (纸本)9781479933587

images captured using consumer grade cameras are missing viable information of image which is depth. This also makes the image to be considered as a two dimensional image. The real life activities like recognition of objects by measuring the distance between objects become very complex and sometimes impossible. Stereo vision imaging, 3-D modeling techniques help to minimize these shortcomings. In this paper we have analyzed various novel works which used the depth information gathered from RGB-D cameras. Microsoft Kinect, a low cost RGB-D sensor has proved to be the most effective of its kind. This paper can provide a clear idea about the extensive research using these sensors that have been going on in the field of augmented Human computer interaction. The exceptional features of these depth sensors can be used to develop more sophisticated applications in the field of computer vision in near future.

关键词： computer vision Kinect sensor depth sensing Indoor 3-D mapping

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Efficient Use of Bandwidth by image Compression for vision-Based Robotic Navigation and Control 3

Efficient Use of Bandwidth by Image Compression for Vision-B...

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3rd international conference on Communications and Signal processing (ICCSP)

作者： Raghavachari, Chakravartula Sundaram, Shanmugha G. A. Amrita Viswa Vidyapeetham Ctr Excellence Computat Engn & Networking Coimbatore 641112 Tamil Nadu India Amrita Viswa Vidyapeetham Dept Elect & Commun Engn Coimbatore 641112 Tamil Nadu India

ISBN: (纸本)9781479933587

In the present modern world, humans are being replaced by computers in almost every field for various beneficial reasons. One such field, where intervention of computers is inevitable and making significant progress is "computer vision", which replicates human vision. In computer vision system, similar to that of an eye, a sensor (a camera) is used to capture the images and different algorithms that usually run on a computer acts as brain for analyzing and understanding features in those captured images. Generally, image is visual representation of information. For better analyzing the information that an image has, many image processing techniques are being used. In real, complete view of an area is always challenging. Here, we are achieving monitoring surroundings of a robot by detecting moving objects from a sequence of panoramic stitched images, which is typically a feature extraction problem in computer vision. By knowing the surrounding environment of a robot, we can enhance its navigation and control. A camera setup, which consists of a single camera or multiple cameras, mounted on the robot is used for acquiring about twenty images, each at an angle of 20 degrees, so as to cover entire 360 degrees images overlapping with the previous image are stitched to get a single panoramic image. Many of such stitched panoramic images can be created for the same scene at different intervals of time and these complete set of stitched images are then processed at the base station for detecting moving objects over that particular scene. So for analyzing the environment by the images acquired, they have to be transferred to the base station by means of a communication channel. Stitching can be done either at the base station or at the on-site. In the earlier case, we need to transfer all the twenty images per interval to the base station but in the latter we just have to send a single stitched image, which reduces the bandwidth usage. Further, using image compression techni

关键词： computer vision image stitching feature extraction image compression

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Implementation of Hough Transform for image processing Applications 3

Implementation of Hough Transform for Image Processing Appli...

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3rd international conference on Communications and Signal processing (ICCSP)

作者： Chandrasekar, L. Durga, G. SSN Coll Engn ECE Dept Madras Tamil Nadu India

ISBN: (纸本)9781479933587

Hough Transform (HT) can provide a significant solution to the problems associated with line detection in an image. Line detection is used to detect the presence of lines in an image, at a particular orientation. The importance of line detection is used for detecting sharp changes in image brightness. HT is a popular technique in computer vision. The HT for line detection replaces the original problem of detecting collinear points in an image space by a simpler task of finding peak points in a parameter space. The proposed method used in this paper is to implement Generalized Hough Transform (GHT) on an image, since in GHT any straight line in the image is represented by a single point in the (p, theta) parameter space and any part of this straight line is transformed into the same point. It can compute the HT of 256 x 256 test images. It can able to detect the lines present in the image and also it can extract feature points in an image.

关键词： Generalized Hough Transform Hough Transform parameter space

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Information Technology in An Improved Moving Target Detection Algorithm

Information Technology in An Improved Moving Target Detectio...

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3rd international conference on Material Science, Environment Science and computer Science (MSESCS 2014)

作者： Zhang, Chunfei Fang, Zhiyi Qu, Haiqin Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China

ISBN: (纸本)9783038350118

Moving target detection is an important research direction in the field of computer vision which is using digital signal processing techniques to extract moving targets from the video image. And the accuracy is directly related to the identification and tracking of the target. Based on the analysis and research of traditional moving target detection algorithm, this paper introduced an improved moving target detection algorithm combined the background subtraction method and mixed-frame difference method, aim to improve the "empty" and "ghosting" phenomenon and achieve the rapid detection of moving targets. Experimental results show the effectives and efficiency of the algorithm.

关键词： image processing Moving Target Detection Background Subtraction Mixed-frame Differencing

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The Recognition of Maize seeds Based on Multi-scale Feature Fusion and Extreme Learning Machine

The Recognition of Maize seeds Based on Multi-scale Feature ...

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2015 3rd international conference on Mechanical Engineering and Intelligent Systems(ICMEIS 2015)

作者： Mingzhi Du Xiao Ke Mingke Zhou College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing (Fuzhou University)

In recognizing traditional crops seeds like maize seeds, we usually use electrophoresis assay method, fluorescence scanning method and chemical assay method. These methods are destructive methods. They take a long time to detect and are demanding of professional background knowledge and hardware conditions etc. What's more, these methods, based on BP neural network and support vector machine(SVM)while taking a long time to detect are less accurate in process of classification. In this paper, based on the computer vision technology, we proposed a new method for the classification of maize seeds, a method based on multi-scale feature fusion and extreme learning machine. First, we extract the multi-scale fusion feature of maize seeds. Second, based on extreme learning machine, we construct the classifier model of maize seed. Third, because of the window of image in the case of multi-scale detection has the problem of capturing the same object seed with many overlapping windows, we put forward a kind of window fusion algorithm to solve it. The simulation results show that: The method is able to identify the maize seeds accurately. Using this method the accuracy of classification of maize seeds can reached 97.66% and the error rate is less than 0.1%. Compared with the traditional methods, the method we proposed can improve the speed of detection and the accuracy of classification, and has no strict hardware requirements.

关键词： extreme learning machine feature fusion object recognition

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