scholarly journals Real-Time Shading Image Implementation Technology for Physical Viod Display

2018 ◽  
Vol 7 (3.34) ◽  
pp. 86
Author(s):  
Eun Seo Song ◽  
Gi Tae Kim ◽  
Sung Dae Hong
Keyword(s):  
Real Time ◽  
Control Structure ◽  
Image Representation ◽  
Image Data ◽  
The Other ◽  
Depth Image ◽  
Control Technology ◽  
Time Data ◽  
Control Solution ◽  
Time Interaction

Background/Objectives: The purpose of this study is control technology to reflect user's appearance and movement in the void display in real time.Methods/Statistical analysis: In this paper, we have developed real-time shading image data acquisition based on RGB-D sensor and real-time interaction image control structure for realizing 0-255 Depth image of physical void display. We also study integrated interlocking control solution for integrated interlocking of hardware and software.Findings: Conventional flip displays show data in 0,1 image representation. On the other hand, the void display we are studying acquires real-time data based on RGB-D and shows the data in depth 0-255 image representation.Improvements/Applications: In the void display, the image representation of 0.1 was extended to the depth 0-255 representation.

scholarly journals Multimodal Art Pose Recognition and Interaction With Human Intelligence Enhancement

2021 ◽  
Vol 12 ◽  
Author(s):  
Chengming Ma ◽  
Qian Liu ◽  
Yaqi Dang
Keyword(s):  
Real Time ◽  
Feature Fusion ◽  
Image Data ◽  
Depth Image ◽  
Hand Gesture ◽  
Depth Information ◽  
Virtual Model ◽  
Global Features ◽  
Pose Recognition ◽  
Time Interaction

This paper provides an in-depth study and analysis of human artistic poses through intelligently enhanced multimodal artistic pose recognition. A complementary network model architecture of multimodal information based on motion energy proposed. The network exploits both the rich information of appearance features provided by RGB data and the depth information provided by depth data as well as the characteristics of robustness to luminance and observation angle. The multimodal fusion is accomplished by the complementary information characteristics of the two modalities. Moreover, to better model the long-range temporal structure while considering action classes with sub-action sharing phenomena, an energy-guided video segmentation method is employed. And in the feature fusion stage, a cross-modal cross-fusion approach is proposed, which enables the convolutional network to share local features of two modalities not only in the shallow layer but also to obtain the fusion of global features in the deep convolutional layer by connecting the feature maps of multiple convolutional layers. Firstly, the Kinect camera is used to acquire the color image data of the human body, the depth image data, and the 3D coordinate data of the skeletal points using the Open pose open-source framework. Then, the action automatically extracted from keyframes based on the distance between the hand and the head, and the relative distance features are extracted from the keyframes to describe the action, the local occupancy pattern features and HSV color space features are extracted to describe the object, and finally, the feature fusion is performed and the complex action recognition task is completed. To solve the consistency problem of virtual-reality fusion, the mapping relationship between hand joint point coordinates and the virtual scene is determined in the augmented reality scene, and the coordinate consistency model of natural hand and virtual model is established; finally, the real-time interaction between hand gesture and virtual model is realized, and the average correct rate of its hand gesture reaches 99.04%, which improves the robustness and real-time interaction of hand gesture recognition.

scholarly journals Target tracking accuracy and latency with different 4D ultrasound systems – a robotic phantom study

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Svenja Ipsen ◽  
Sven Böttger ◽  
Holger Schwegmann ◽  
Floris Ernst
Keyword(s):  
Target Tracking ◽  
Real Time ◽  
Template Matching ◽  
Image Data ◽  
Distinct Advantage ◽  
Reference Trajectory ◽  
Data Streaming ◽  
Tracking Accuracy ◽  
Time Data ◽  
4D Ultrasound

AbstractUltrasound (US) imaging, in contrast to other image guidance techniques, offers the distinct advantage of providing volumetric image data in real-time (4D) without using ionizing radiation. The goal of this study was to perform the first quantitative comparison of three different 4D US systems with fast matrix array probes and real-time data streaming regarding their target tracking accuracy and system latency. Sinusoidal motion of varying amplitudes and frequencies was used to simulate breathing motion with a robotic arm and a static US phantom. US volumes and robot positions were acquired online and stored for retrospective analysis. A template matching approach was used for target localization in the US data. Target motion measured in US was compared to the reference trajectory performed by the robot to determine localization accuracy and system latency. Using the robotic setup, all investigated 4D US systems could detect a moving target with sub-millimeter accuracy. However, especially high system latency increased tracking errors substantially and should be compensated with prediction algorithms for respiratory motion compensation.

scholarly journals Real-Time and Offline Evaluation of Myoelectric Pattern Recognition for the Decoding of Hand Movements

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5677
Author(s):  
Sara Abbaspour ◽  
Autumn Naber ◽  
Max Ortiz-Catalan ◽  
Hamid GholamHosseini ◽  
Maria Lindén
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Classification Accuracy ◽  
Likelihood Estimation ◽  
The Other ◽  
Time Data ◽  
Linear Discriminant ◽  
Time Performance ◽  
Performance Metric ◽  
Upper Limb Prostheses

Pattern recognition algorithms have been widely used to map surface electromyographic signals to target movements as a source for prosthetic control. However, most investigations have been conducted offline by performing the analysis on pre-recorded datasets. While real-time data analysis (i.e., classification when new data becomes available, with limits on latency under 200–300 milliseconds) plays an important role in the control of prosthetics, less knowledge has been gained with respect to real-time performance. Recent literature has underscored the differences between offline classification accuracy, the most common performance metric, and the usability of upper limb prostheses. Therefore, a comparative offline and real-time performance analysis between common algorithms had yet to be performed. In this study, we investigated the offline and real-time performance of nine different classification algorithms, decoding ten individual hand and wrist movements. Surface myoelectric signals were recorded from fifteen able-bodied subjects while performing the ten movements. The offline decoding demonstrated that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) significantly (p < 0.05) outperformed other classifiers, with an average classification accuracy of above 97%. On the other hand, the real-time investigation revealed that, in addition to the LDA and MLE, multilayer perceptron also outperformed the other algorithms and achieved a classification accuracy and completion rate of above 68% and 69%, respectively.

A Virtual Reality Drumkit Simulator System with a Kinect Device

2015 ◽  
Vol 6 (1) ◽  
pp. 72-86 ◽  
Author(s):  
Alejandro Rosa-Pujazón ◽  
Isabel Barbancho ◽  
Lorenzo J. Tardón ◽  
Ana M. Barbancho
Keyword(s):  
Machine Learning ◽  
Virtual Reality ◽  
Real Time ◽  
User Experience ◽  
The Other ◽  
Wiener Filtering ◽  
Detection Model ◽  
Time Interaction ◽  
Kinect Camera ◽  
Drumkit Simulator

In this paper, an implementation of a virtual reality based application for drumkit simulation is presented. The system tracks user motion through the use of a Kinect camera sensor, and recognizes and detects user-generated drum-hitting gestures in real-time. In order to compensate the effects of latency in the sensing stage and provide real-time interaction, the system uses a gesture detection model to predict user movements. The paper discusses the use of two different machine learning based solutions to this problem: the first one is based on the analysis of velocity and acceleration peaks, the other solution is based on Wiener filtering. This gesture detector was tested and integrated into a full implementation of a drumkit simulator, capable of discriminating up to 3, 5 or 7 different drum sounds. An experiment with 14 participants was conducted to assess the system's viability and impact on user experience and satisfaction.

Fault detection for control of wastewater treatment plants

2006 ◽  
Vol 53 (4-5) ◽  
pp. 375-382 ◽  
Author(s):  
O. Schraa ◽  
B. Tole ◽  
J.B. Copp
Keyword(s):  
Wastewater Treatment ◽  
Process Control ◽  
Real Time ◽  
Control Structure ◽  
Wastewater Treatment Plants ◽  
Process Models ◽  
Sensor Data ◽  
Time Data ◽  
Model Based Control ◽  
Model Based

Interest in real-time model-based control is increasing as more and more facilities are being asked to meet stricter effluent requirements while at the same time minimizing costs. It has been identified that biological process models and automated process control technologies are being used at wastewater treatments plants throughout the world and that great potential for optimising biotreatment may exist with the integration of these two technology areas. According to our experience, wastewater treatment plants are indeed looking for ways to successfully integrate their modelling knowledge into their process control structure; however, there are practical aspects of this integration that must be addressed if the benefits of this integration are to be realised. This paper discusses the practical aspects of monitoring, filtering and analysing real sensor data with an aim to produce a reliable real-time data stream that might be used within a model-based control structure. Several real case study examples are briefly discussed in this paper.

scholarly journals Real-Time Image Transmission Algorithm in WSN with Limited Bandwidth

2018 ◽  
Vol 14 (12) ◽  
pp. 57
Author(s):  
Hui Huang ◽  
Zhe Li
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Network Architecture ◽  
Monitoring Network ◽  
Image Data ◽  
Image Transmission ◽  
Time Data ◽  
Limited Bandwidth ◽  
Real Time Image ◽  
Time Image

In this paper, a real-time image transmission algorithm in WSN with limited bandwidth networks is studied. Firstly, a simple and effective monitoring network architecture is established, which allows multiple video monitoring nodes to access the network, and the data transmission is controlled by the synchronization mechanism without collision. Then, the image data is compressed locally at the monitoring nodes (over 85%), so that the image of each node can meet the needs of real-time data transmission, and the overall power consumption of the system is greatly reduced. Finally, based on NVIDIA TX1, four test nodes are constructed to test the algorithm cumulatively, which verifies the effectiveness of the system framework and compression algorithm.

scholarly journals Technological Support of Real-Time Interaction in Web Clients of Analytical Fraud Detection Systems

2018 ◽  
Vol 3 (2) ◽  
pp. 450
Author(s):  
Radygin V.Y. ◽  
Kupriyanov D. Yu
Keyword(s):  
Real Time ◽  
Data Exchange ◽  
Fraud Detection ◽  
Time Data ◽  
Web Based ◽  
Technological Support ◽  
Detection Systems ◽  
Time Interaction ◽  
Client Software ◽  
Detection Software

The optimal tools selection for design of web-based visual mining client for real time fraud detection systems was discussed. The features of modern real time fraud detection software were analyzed. The necessity of transition to using of web-based technologies for client software design was shown. The market of web-frameworks and browser to web-server data exchange technologies were investigated. Basing on experimental research the most efficient toolset for design of web-client software for real time fraud detection systems was offered. Keywords: fraud detection, Visual Mining, real time data exchange, web-visualization, webSockets, MessageBus.

scholarly journals Research on Body Positioning Measurement Method of Bolting Robot based on Vision Theory

2021 ◽  
Author(s):  
Xuedi Hao ◽  
Xueqiang Yang ◽  
Jinglin Zhang ◽  
Yaotian Ding ◽  
Miao Wu
Keyword(s):  
Real Time ◽  
Image Data ◽  
Monocular Vision ◽  
Vehicle Body ◽  
Positioning System ◽  
System Transformation ◽  
Time Data ◽  
Experimental Conditions ◽  
Vision Positioning ◽  
Body Positioning

Abstract In view of the intelligent demand of underground roadway support and the precise positioning of underground unmanned fully mechanized face, a method of body positioning measurement of bolting robot based on the principle of monocular vision is proposed. In this paper, a vehicle body positioning model based on image data is established. The data is obtained by camera, and the transformation between image coordinates and world coordinates is completed by coordinate system transformation. The monocular vision positioning system of bolting robot is designed, and the simulation experimental model is built to measure the effective positioning distance of monocular vision positioning system in the simulation experimental conditions. The experimental platform of bolting robot is designed, and the vehicle is measured Real time data of body positioning, analysis of experimental error and demonstration of reliability of the method. In this method, the real-time localization of underground mine is realized by the robot of bolting, and the accuracy and efficiency of localization are improved, which lays the foundation for the localization control of mining face and the automation and unmanned of the robot of bolting.

Design of Data Acquisition System Based on FPGA

2011 ◽  
Vol 403-408 ◽  
pp. 1592-1595
Author(s):  
Guo Sheng Xu
Keyword(s):  
Data Processing ◽  
Data Acquisition ◽  
Real Time ◽  
High Speed ◽  
Image Data ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Time Data ◽  
Real Time Processing ◽  
Field Programmable

A new kind of data acquisition system is introduced in this paper, in which the multi-channel synchronized real-time data acquisition under the coordinate control of field-programmable gate array(FPGA) is realized. The design uses field programmable gate arrays(FPGA) for the data processing and logic control. For high speed CCD image data processing, the paper adopts regional parallel processing based on FPGA. The FPGA inner block RAM is used to build high speed image data buffer is put into operation to achieve high speed image data integration and real-time processing. The proposed data acquisition system has characteristics of stable performance, flexible expansion, high real-timeness and integration

Ambulatory Assessment

2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull
Keyword(s):  
Real Time ◽  
Clinical Psychology ◽  
Real Life ◽  
Ambulatory Assessment ◽  
Computer Assisted ◽  
Affective Valence ◽  
Time Data ◽  
Physiological Processes ◽  
Context Specific ◽  
Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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