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IEEE international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Run Ye Chao Tao Bin Yan Ting Yang School of Automation Engineering University of Electronic Science and Technology of China Chengdu P. R. China

ISBN: (数字)9781728198279

ISBN: (纸本)9781728181585

In order to ensure that the Unmanned Aerial Vehicle (UAV) achieves a safe and accurate landing under special conditions such as GPS signal interference, an autonomous landing method based on computer vision is proposed. Firstly, the projection model of the airborne camera is established, and the camera's internal parameter matrix is obtained by camera calibration. Then, the “H” landing target pattern is designed to reduce the complexity of image processing, and the white backing disc is added to make the background easier to the segment. Then the pose estimation model is established and combined with the coordinate information of the feature points to complete the pose calculation. Finally, the actual flight data of the UAV is compared with the pose estimation data, and the maximum error of the position and attitude estimation values is 0. 52m and 6.22°, which can basically meet the landing requirements of the UAV, and the feasibility of the method is proved.

关键词： Feature extraction Cameras Unmanned aerial vehicles Shape Visualization Radio navigation Global navigation satellite system

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Proposal of Effective Orthogonal and Hexagonal Hierarchical Structures for Disc Queries

Proposal of Effective Orthogonal and Hexagonal Hierarchical ...

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international conference on Cybernetics, Robotics and Control (CRC)

作者： Vojtěch Uher Petr Gajdoš Václav Snášel Department of Computer Science VŠB-Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9781538677391

The Fixed-Radius Nearest Neighbors (FRNN) query is a common task in scientific areas dealing with multidimensional point clouds (PCs) such as computer graphics, image processing, geographic information systems, machine learning and pattern recognition. We especially focus on 2D points in this paper. The FRNN means search all the points within defined radius for tasks when local properties of data are crucial. As this procedure is time consuming, an effective accelerating structure indexing the points is required. The standard methods are based on the orthogonal grids subdividing the space into uniform cells or hierarchies of orthogonal grids. However, several papers highlight the regular hexagonal grids for their superior theoretical metrics, e.g. better coverage of query discs, uniform distance to all six neighbors or lower number of passed cells. This paper provides a comparison of effectiveness of orthogonal and hexagonal hierarchies and traditional algorithms for FRNN disc queries. To do this, we propose a novel hierarchical method based on the hexagonal space-filling curve called the Node-Gosper curve which defines the hierarchical location of points in the hexagonal grids and their linear order. This method is tested with similar structure based on the orthogonal Z-order curve to show the real features of both approaches in practice.

关键词： Three-dimensional displays Vegetation Two dimensional displays Fractals Task analysis Shape Standards

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2020年 1022 AISC卷 v-vi页

作者： Chaudhuri, Bidyut B. Nakagawa, Masaki Khanna, Pritee Kumar, Sanjeev Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Techno India University Kolkata India Department of Advanced Information Technology and Computer Sciences Tokyo Institute of Agriculture and Technology Koganei Tokyo Japan Department of Computer Science Indian Institute of Information Technology Design and Manufacturing Jabalpur Jabalpur Madhya Pradesh India Department of Mathematics Indian Institute of Technology Roorkee Roorkee Uttarakhand India

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Impact of Font on computer Recognition of License Plates on Automobiles 2019

Impact of Font on Computer Recognition of License Plates on ...

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Proceedings of the 3rd international conference on vision, image and Signal processing

作者： Rabiah Al-qudah Ching Y. Suen Computer Science Concordia University Montreal QC Canada Computer Science Concordia University Montreal QC Canada

ISBN: (纸本)9781450376259

The chosen font type in the license plate (LP) plays a vital role in the recognition phase in computer-based operations. Some fonts are challenging for humans to read; however, other fonts are challenging for computer systems to recognize. Here, we present two sets of results for font evaluation: font anatomy results, and recognition results for commercial products. For anatomy results, two typical LP fonts are considered: Mandatory, and Driver Gothic. Moreover, we evaluate the effect of these fonts in context for two datasets using two commercial products: OpenALPR and Plate Recognizer. The font anatomy results revealed some important confusion cases and some quality features of both fonts. The obtained results show that the Driver font has less severe confusion cases than the Mandatory font.

关键词： Recognition Font analysis License plate Error analysis

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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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Evaluation of business english majors teaching quality based on the attribute importance of rough set 2019

Evaluation of business english majors teaching quality based...

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3rd international Workshop on Education, Big Data and Information Technology, EBDIT 2019

作者： Fan, Yanying Jiang, Suping Zhang, Zimin Chen, Guanping Chen, Yangming Li, Biqing College of Mathematics and Computer Hezhou University Hezhou Guangxi542899 China Guangxi Talent International College Qinzhou Guangxi535000 China College of Tourism and Sports Hezhou University Hezhou542899 China School of Mathematics and Computer Science Hezhou University Hezhou542899 China School of Information and Communication Engineering Hezhou University Hezhou Guangxi542899 China

ISBN: (纸本)9781450372053

Aiming at the unreasonable weight allocation in traditional teaching evaluation, rough set theory (RST) is applied to the process of teaching evaluation. Using the Teaching Quality evaluation data of Business English Majors from Guangxi Talent international College, we establish the evaluation information system, and calculate the importance of evaluation index, based on which, the weight of index is calculated. Finally, the evaluation results are calculated according to the weight of index. The weight of rough set index is determined entirely by the data itself, avoiding the influence of subjective factors, so it is more scientific, reasonable, objective and fair. © 2019 Association for Computing Machinery.

关键词： Rough set theory

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Smart Surveillance Object Detection System

Smart Surveillance Object Detection System

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Artificial Intelligence For Internet of Things (AIIoT), international conference on

作者： Gaurav Chaudhary Shreya Pathak Vikas Choudhary Love Chauhan Abhishek N Tripathi School of Electronics Engineering Vellore Institute of Technology Vellore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Vellore India

ISBN: (数字)9798350372120

ISBN: (纸本)9798350372137

This paper presents an integrated Internet of Things based approach to smart surveillance and urban parking management systems, emphasizing robust object detection and precise parking occupancy monitoring. Our solution adopts cost-effective hardware like the ESP32 CAM module, leveraging its built-in camera and powerful processor for real-time image processing. For surveillance applications, we implement a custom object detection model built with OpenCV, a renowned Python library. This model, finely-tuned for efficient person detection, runs directly on the ESP32 CAM, eliminating the need for external processing units. Additionally, the ESP32 CAM’s Wi-Fi connectivity enables seamless integration with existing networks, simplifying deployment. This integrated approach, combining the cost-effectiveness of ESP32 CAM modules with the image processing capabilities of OpenCV, offers a comprehensive solution for smart surveillance and urban parking management. By utilizing readily available hardware and open-source software, the system promotes widespread adoption and affordability, making it a valuable tool for creating smarter and more sustainable cities.

关键词： computer vision Surveillance Object detection Real-time systems Libraries Hardware Internet of Things

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Camera Pose Estimation using CNN 20

Camera Pose Estimation using CNN

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Proceedings of the 3rd international conference on Control and computer vision

作者： Bhattarabhorn Wattanacheep Orachat Chitsobhuk King Mongkut's Institute of Technology Ladkrabang Thailand

ISBN: (纸本)9781450388023

Estimating camera pose is a significant process, which assures the success of the 3D modeling performance. This research presents a camera pose estimation using convolutional neural network (CNN) to transfer learning from pre-trained deep learning VGG19 model in order to extract features from a single image using several datasets captured in indoor and outdoor environments with diverse perspectives and photographic styles. Due to the large dimensions of the extracted features, Latent Semantic Analysis (LSA) are introduced prior to the CNN input. Then, the CNN is trained to predict the camera views and translations. The prediction performance is measured in terms of average mean square errors and compared to the reference techniques. As a result, the regression estimation of the proposed CNN model outperforms the others with average 0.24 degrees rotation error and 0.26 m. translation errors.

关键词： Deep Learning image processing Robotics 3D Reconstruction

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Crackvision: A Fusion of Deep Learning and image processing for Comprehensive Wall Crack Detection and Analysis

CrackVision: A Fusion of Deep Learning and Image Processing ...

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Artificial Intelligence For Internet of Things (AIIoT), international conference on

作者： Yaythish Kannaa G S Dennis Joshua D Ganesh Kumar Chellamani Manoj Prabhakaran K Department of Electronics and Communication Engineering Amrita School of Engineering Chennai Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350372120

ISBN: (纸本)9798350372137

Wall crack detection is an essential part of the maintenance of building and safety as it allows for identifying and assessing defects on the wall surface. This information is necessary for determining the extent of the crack and the correct repair or reinforcement measures to be taken. Early methods, such as visual inspection, have been used, but recent advances in technology, such as infrared thermography and acoustic emission testing, have proven the detection of the crack. But in recent days, machine learning and computer vision techniques have become potent tools for automating and enhancing wall crack detection *** paper presents wall crack detection, combining image processing and deep learning. The edge detection algorithms like canny edge detector and You Only Look Once (YOLO) object detection models are implemented on the high-performance Nvidia Jetson Nano platform. This combination achieved an impressive 97.3% accuracy, demonstrating the effectiveness of the implemented methodology. Not only does the YOLO model increase the efficiency of wall crack detection, but it also improves the overall reliability of inspection procedures. This research is a step forward in utilizing cutting-edge technologies to solve critical building maintenance and safety aspects of the building.

关键词： YOLO Deep learning Accuracy Computational modeling image processing image edge detection Buildings

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Robust Temporal Super-Resolution for Dynamic Motion Videos

Robust Temporal Super-Resolution for Dynamic Motion Videos

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international conference on computer vision Workshops (ICCV Workshops)

作者： Bumjun Park Songhyun Yu Jechang Jeong Department of Electronics and Computer Engineering Hanyang University Seoul Republic of Korea Department of Electronic Engineering Hanyang University Seoul Republic of Korea

ISBN: (数字)9781728150239

ISBN: (纸本)9781728150246

It is difficult to apply most video temporal super-resolution studies for real-world scenes because they are optimized for a specific range of characteristics. In this paper, we propose a video temporal super-resolution method that is tolerant to motion diversity and noise. Our proposed method improves its robustness by fine-tuning the pre-trained SPyNet that is trained for videos with simple motions and moderate conditions. Moreover, our proposed network learns to accurately synthesize two frames generated by a backward warping function without requiring any additional information using the architecture of a modified DHDN. This enables our proposed method to efficiently synthesize two warped frames by saving the computational complexity for pre-training and extracting the additional information. Finally, we apply the self-ensemble method, which is commonly used in studies on image processing but not on video processing. The application of the self-ensemble method enables our network to generate stable output frames with improved quality without any additional training. Our proposed network proved its performance by ranking 5th in the AIM 2019 video temporal super-resolution challenge; the performance gap between our proposed network and the 3rd-and 4th-ranked solutions was very small. The source code and pre-trained models are available at https://***/BumjunPark/DVTSR.

关键词： Videos Optical flow Training Dynamics Feature extraction Robustness computer architecture

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