检索结果-内蒙古大学图书馆

visual data processing Framework for a Skin-Based Human Detection 1

6th International Conference on Interactive Collaborative Robotics (ICR)

作者： Myrzin, Valery Tsoy, Tatyana Bai, Yang Svinin, Mikhail Magid, Evgeni Kazan Fed Univ Inst Informat Technol & Intelligent Syst Intelligent Robot Dept Lab Intelligent Robot Syst LIRS Kazan Russia Ritsumeikan Univ Coll Informat Sci & Engn Informat Sci & Engn Dept 1-1-1 Noji Higashi Kusatsu Shiga 5258577 Japan

ISBN: (数字)9783030877255

ISBN: (纸本)9783030877255;9783030877248

For a large variety of tasks autonomous robots require a robust visual data processing system. This paper presents a new human detection framework that combines rotation-invariant histogram of oriented gradients (RIHOG) features and binarized normed gradients (BING) pre-processing and skin segmentation. For experimental evaluation a new Human body dataset of over 60000 images was constructed using the Human-Parts dataset, the Simulated disaster victim dataset, and the Servosila Engineer robot dataset. Random, Liner SVM, Quadratic SVM, AdaBoost, and Random Forest approaches were compared using the Human body dataset. Experimental evaluation demonstrated an average precision of 90.4% for the Quadratic SVM model and showed the efficiency of RIHOG features as a descriptor for human detection tasks.

关键词： visual data processing Skin segmentation Feature extraction Image classification Mobile robot

来源：评论

学校读者我要写书评

暂无评论

Energy-aware Mobile Edge Computing for Low-Latency visual data processing 5

Energy-aware Mobile Edge Computing for Low-Latency Visual Da...

引用

IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud)

作者： Huy Trinh Chemodanov, Dmitrii Yao, Shizeng Lei, Qing Zhang, Bo Gao, Fan Calyam, Prasad Palaniappan, Kannappan Univ Missouri Columbia MO 65211 USA

ISBN: (纸本)9781538620748

New opportunities exist for applications such as disaster incident response that can benefit from the convergence of Internet of Things (IoT) and cloud computing technologies. Particularly, new paradigms such as Mobile Edge Computing (MEC) are becoming feasible to handle the data deluge occurring in the network edge to gain insights that assist in real-time decision making. In this paper, we study the potential of MEC to address application issues related to energy management on constrained IoT devices with limited power sources, while also providing low-latency processing of visual data being generated at high resolutions. Using a face recognition application that is important in disaster incident response scenarios, we analyze the tradeoffs in computing policies that offload visual data processing (i.e., to an edge cloud or a core cloud) at low-to high workloads, and their impact on energy consumption under different visual data consumption requirements (i.e., users with thick clients or thin clients). From our empirical results obtained from experiments with our face recognition application on a realistic edge and core cloud testbed, we show how MEC can provide flexibility to users who desire energy conservation over low-latency or vice versa in the visual data processing.

关键词： IoT-based applications cloud computing energy awareness visual data processing mobile edge cloud

来源：评论

学校读者我要写书评

暂无评论

A Survey on Sensor Coverage and visual data Capturing/processing/Transmission in Wireless visual Sensor Networks

引用

SENSORS 2014年第2期14卷 3506-3527页

作者： Yap, Florence G. H. Yen, Hong-Hsu Chang Gung Univ English Div Ctr Gen Educ Taoyuan 333 Taiwan Shih Hsin Univ Dept Informat Management Taipei 116 Taiwan

Wireless visual Sensor Networks (WVSNs) where camera-equipped sensor nodes can capture, process and transmit image/video information have become an important new research area. As compared to the traditional wireless sensor networks (WSNs) that can only transmit scalar information (e.g., temperature), the visual data in WVSNs enable much wider applications, such as visual security surveillance and visual wildlife monitoring. However, as compared to the scalar data in WSNs, visual data is much bigger and more complicated so intelligent schemes are required to capture/process/transmit visual data in limited resources (hardware capability and bandwidth) WVSNs. WVSNs introduce new multi-disciplinary research opportunities of topics that include visual sensor hardware, image and multimedia capture and processing, wireless communication and networking. In this paper, we survey existing research efforts on the visual sensor hardware, visual sensor coverage/deployment, and visual data capture/processing/transmission issues in WVSNs. We conclude that WVSN research is still in an early age and there are still many open issues that have not been fully addressed. More new novel multi-disciplinary, cross-layered, distributed and collaborative solutions should be devised to tackle these challenging issues in WVSNs.

关键词： sensor coverage visual data capturing visual data processing visual data transmission wireless visual sensor networks

来源：评论

学校读者我要写书评

暂无评论

A Lite Fireworks Algorithm with Fractal Dimension Constraint for Feature Selection 6

A Lite Fireworks Algorithm with Fractal Dimension Constraint...

引用

IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)

作者： Zeng, Min Mo, Haimiao Liang, Zhiming Wang, Hua Guangdong Univ Sci & Technol Sch Comp Sci Dongguan Guangdong Peoples R China Hefei Univ Technol Sch Management Hefei Peoples R China Guangzhou Med Univ Affiliated Hosp 5 Dept Pharm Guangzhou Guangdong Peoples R China

ISBN: (纸本)9798350311259

As the use of robotics becomes more widespread, the huge amount of vision data leads to a dramatic increase in data dimensionality. Although deep learning methods can effectively process these high-dimensional vision data. Due to the limitation of computational resources, some special scenarios still rely on traditional machine learning methods. However, these high-dimensional visual data lead to great challenges for traditional machine learning methods. Therefore, we propose a Lite Fireworks Algorithm with Fractal Dimension constraint for feature selection (LFWA+FD) and use it to solve the feature selection problem driven by robot vision. The "LFWA+FD" focuses on searching the ideal feature subset by simplifying the fireworks algorithm and constraining the dimensionality of selected features by fractal dimensionality, which in turn reduces the approximate features and reduces the noise in the original data to improve the accuracy of the model. The comparative experimental results of two publicly available datasets from UCI show that the proposed method can effectively select a subset of features useful for model inference and remove a large amount of noise noise present in the original data to improve the performance.

关键词： visual data processing Feature Selection Fractal Dimension Fireworks Algorithm

来源：评论

学校读者我要写书评

暂无评论

Effective hybrid video denoising and blending framework for Internet of Remote Things (IoRT) environments

引用

AUTOMATIKA 2024年第2期65卷 510-522页

作者： Devi, B. Aruna Choudhry, Mani Deepak Dr NGP Inst Technol Dept Elect & Commun Engn Coimbatore India KGiSL Inst Technol Dept Informat Technol Coimbatore India

The Internet of Remote Things (IoRT) has emerged as a transformative paradigm, merging IoT capabilities with remote technologies. IoRT environments, featuring interconnected sensors and robots, face challenges like sensor noise and low-light conditions, compromising video stream quality. This paper proposes a Hybrid Video Denoising and Blending Framework to address IoRT video data shortcomings. Leveraging spatial and temporal domain denoising techniques, the framework effectively removes noise while preserving crucial details. The inclusion of advanced blending algorithms facilitates seamless fusion of data from multiple sources, enhancing decision-making in real-world scenarios. The framework adopts a dynamic weighted averaging approach and an optimal sensor selection mechanism to intelligently choose informative data sources, improving blended output quality. Extensive experiments with a diverse IoRT dataset showcase the framework's superiority over state-of-the-art techniques, offering significant enhancements in video quality, noise reduction, and data fusion accuracy. Applications like surveillance, autonomous remotes, and industrial automation can benefit from the framework's ability to provide clearer, more reliable visual information. In conclusion, this research introduces a pioneering approach to mitigate video noise and enhance data fusion in IoRT, showcasing promising results and paving the way for further research in the integration of Remotes and IoT.

关键词： Internet of Remote Things (IoRT) real-time processing noise reduction video quality enhancement visual data processing reliability and accuracy

来源：评论

学校读者我要写书评

暂无评论

Urban Wind Corridors Analysis via Network Theory

引用

ATMOSPHERE 2023年第3期14卷 572页

作者： Nevat, Ido Adelia, Ayu Sukma TUMCREATE Singapore 138602 Singapore Singapore ETH Ctr Singapore 138602 Singapore

We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design.

关键词： urban canopy wind visual data processing meso-scale climate simulation network theory graph theory Least Cost Path (LCP)

来源：评论

学校读者我要写书评

暂无评论

SPATIALLY REGULARIZED LOW RANK TENSOR OPTIMIZATION FOR visual data COMPLETION 25

SPATIALLY REGULARIZED LOW RANK TENSOR OPTIMIZATION FOR VISUA...

引用

25th IEEE International Conference on Image processing (ICIP)

作者： Gao, Jianchao Shi, Hong Wang, Wenwu Tianjin Univ Sch Comp Sci & Technol Tianjin Peoples R China Univ Surrey Dept Elect & Elect Engn Guildford Surrey England

ISBN: (纸本)9781479970612

Low-rank tensor completion is a recent method for estimating the values of the missing elements in tensor data by minimizing the tensor rank. However, with only the low rank prior, the local piecewise smooth structure that is important for visual data is not used effectively. To address this problem, we define a new spatial regularization S-norm for tensor completion in order to exploit the local spatial smoothness structure of visual data. More specifically, we introduce the S-norm to the tensor completion model based on a non-convex LogDet function. The S-norm helps to drive the neighborhood elements towards similar values. We utilize the Alternating Direction Method of Multiplier (ADMM) to optimize the proposed model. Experimental results in visual data demonstrate that our method outperforms the state-of-the-art tensor completion models.

关键词： tensor completion S-norm LogDet function low rank visual data processing

来源：评论

学校读者我要写书评

暂无评论

Technology of Developing the Software for Robots Vision Systems 16

Technology of Developing the Software for Robots Vision Syst...

引用

16th International Conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Sokolov, S. M. Boguslavsky, A. A. Beklemichev, N. D. RAS Keldysh Inst Appl Math Miusskaya Sq 4 Moscow Russia

ISBN: (纸本)9789897583803

The article describes the technology of developing the software for real-time vision systems. The article shows the position of this technology in the existing software tools. This technology is based on a unified software framework. This framework is an application model that implements the input and processing of the real time visual data. The framework structure provides prompt reprocessing for use in specific application tasks and is focused on the real time visual data processing. The article provides examples of vision systems based on the described framework. In addition, as the analysis shows, this framework can be jointly used with the ROS software through processing as a part of a separate ROS node.

关键词： Vision Systems Real-time Systems Software Framework visual data processing Robot Software ROS

来源：评论

学校读者我要写书评

暂无评论

ClickPoints: an expandable toolbox for scientific image annotation and analysis

引用

METHODS IN ECOLOGY AND EVOLUTION 2017年第6期8卷 750-756页

作者： Gerum, Richard C. Richter, Sebastian Fabry, Ben Zitterbart, Daniel P. Univ Erlangen Nurnberg BioPhys Grp Erlangen Germany Woods Hole Oceanog Inst Appl Ocean Phys & Engn Woods Hole MA 02543 USA Helmholtz Ctr Polar & Marine Res Alfred Wegener Inst Bremerhaven Germany

1. Optical recordings are ubiquitous in current scientific research. As recording and storing images and videos have become simpler and cheaper over the past years, new and more efficient tools are needed to analyse the growing amount of data. While current scientific image analysis tools focus on medical 3D data sets, a tool for efficiently handling large-scale 2D time-series recordings is still missing. 2. We developed Click Points, an expandable, open-source, Python-based software to fill this gap. ClickPoints combines and streamlines the three main steps of image analysis - visualization, annotation and evaluation - in one program. 3. ClickPoints enables the user to (i) efficiently review large data sets of images and videos, (ii) annotate interesting findings and (iii) facilitate manual and automatic evaluations. ClickPoints is highly versatile, ranging from clicking and selecting objects with simple markers, drawing masks and computing trajectories, up to (iv) custom-written Python add-ons for adapting or extending the available features. These add-ons (v) reduce development time by utilizing Click Points' display, interface and storage solutions. In addition, ClickPoints provides an (vi) extensive data base application programming interface to facilitate efficient storage and retrieval of results. 4. ClickPoints is designed to simplify repetitive and labour-intensive scientific tasks, especially when dealing with large image and video time-series recordings. ClickPoints offers cross-platform support for Windows and Linux and is released under the GPLv3 license. Download, documentation and numerous examples are available at http://***.

关键词： ground truth image annotation image evaluation labelling open source Python time-series data visual data processing

来源：评论

学校读者我要写书评

暂无评论

SoF-SLAM: Segments-on-Floor-based Monocular SLAM

SoF-SLAM: Segments-on-Floor-based Monocular SLAM

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Zhang, Guoxuan Suh, Il Hong Hanyang Univ Coll Engn Div Comp Sci & Engn Seoul South Korea

ISBN: (纸本)9781424466757

In this paper, we propose a novel monocular SLAM method in corridor environment which employs Segments-on-Floor (SoF) as feature data. Given that the height of the camera and the angle between the camera and the floor are known, an image of the SoF can be efficiently distinguished from the other space-lines by a simple data-association method, deriving the line correspondence from a simplified homography matrix of two sequentially gathered images. Furthermore, use of SoF simplifies the analysis of the geometrical property of the camera projection matrix. Therefore, we can reconstruct SoF by using a one-step inverse projection. Once SoF is calculated from visual data processing, they are then used in a normal SLAM process as feature data. We employ a simple particle filter in our corridor SLAM. Experimental results show that it is sufficient for mapping a moderately sized building environment.

关键词： SLAM (robots) SoF-SLAM camera height camera projection matrix cameras data visualisation data-association method geometrical property homography matrix matrix algebra monocular SLAM one-step inverse projection particle filter particle filtering (numerical methods) robot vision segments-on-floor sensor fusion visual data processing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：