scholarly journals Intelligent textiles: designing a gesture-controlled illuminated textile based on computer vision

2021 ◽  
pp. 004051752110342
Author(s):  
Jeanne Tan ◽  
Li Shao ◽  
Ngan Yi Kitty Lam ◽  
Anne Toomey ◽  
Lan Ge
Keyword(s):  
Computer Vision ◽  
Open Source ◽  
Gesture Recognition ◽  
Design Method ◽  
Stripe Pattern ◽  
Textile Design ◽  
Weave Structure ◽  
Recognition Function ◽  
Intelligent Technology ◽  
Novel Design

Artificial intelligence (AI) offers the potential for the development of e-textiles that give wearers a smart and intuitive experience. An emerging challenge in intelligent materials design is hand gesture recognition textiles. Most current research focuses on number gesture recognition via smart gloves, so there is a gap in research that studies contact-less number gesture recognition textiles via computer vision. Meanwhile, there is lack of exploration on the integration of illuminating function and number gesture recognition textiles to improve interactivity by real-time visualizing detection results. In this research, a novel interactive illuminating textile with a touch-less number gesture recognition function has been designed and fabricated by using an open-source AI model. It is used in sync with a polymeric optical fiber textile with illuminative features. The textile is color-changing, controlled by the system's mid-air interactive number gesture recognition capability and has a woven stripe pattern and a double-layer weave structure with open pockets to facilitate integration of the system's components. Also described here is a novel design process that permits textile design and intelligent technology to integrate seamlessly and in synchronization, so that design in effect mediates continuously between the physical textile and the intangible technology. Moreover, this design method serves as a reference for the integration of open-source intelligent hardware and software into e-textiles for enhancement of the intuitive function and value via economy of labor.

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Feature Detection ◽  
Video Stream ◽  
Object Identification ◽  
Vision Systems ◽  
Modern Computer ◽  
Computer Vision Systems ◽  
Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

scholarly journals Lightweight and maintainable rotary-wing UAV frame from configurable design to detailed design

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110349
Author(s):  
Huiqiang Guo ◽  
Mingzhe Li ◽  
Pengfei Sun ◽  
Changfeng Zhao ◽  
Wenjie Zuo ◽  
...  
Keyword(s):  
Design Method ◽  
Geometric Model ◽  
Optimization Method ◽  
Frame Structure ◽  
Manufacturing Cost ◽  
Detailed Design ◽  
High Manufacturing Cost ◽  
The Military ◽  
Rotary Wing ◽  
Novel Design

Rotary-wing unmanned aerial vehicles (UAVs) are widespread in both the military and civilian applications. However, there are still some problems for the UAV design such as the long design period, high manufacturing cost, and difficulty in maintenance. Therefore, this paper proposes a novel design method to obtain a lightweight and maintainable UAV frame from configurable design to detailed design. First, configurable design is implemented to determine the initial design domain of the UAV frame. Second, topology optimization method based on inertia relief theory is used to transform the initial geometric model into the UAV frame structure. Third, process design is considered to improve the manufacturability and maintainability of the UAV frame. Finally, dynamic drop test is used to validate the crashworthiness of the UAV frame. Therefore, a lightweight UAV frame structure composed of thin-walled parts can be obtained and the design period can be greatly reduced via the proposed method.

scholarly journals End-To-End Computer Vision Framework: An Open-Source Platform for Research and Education

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3691
Author(s):  
Ciprian Orhei ◽  
Silviu Vert ◽  
Muguras Mocofan ◽  
Radu Vasiu
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Computer Vision ◽  
Open Source ◽  
Visual Processing ◽  
Research Field ◽  
Learning Models ◽  
Research Activity ◽  
End To End ◽  
Machine Learning Models

Computer Vision is a cross-research field with the main purpose of understanding the surrounding environment as closely as possible to human perception. The image processing systems is continuously growing and expanding into more complex systems, usually tailored to the certain needs or applications it may serve. To better serve this purpose, research on the architecture and design of such systems is also important. We present the End-to-End Computer Vision Framework, an open-source solution that aims to support researchers and teachers within the image processing vast field. The framework has incorporated Computer Vision features and Machine Learning models that researchers can use. In the continuous need to add new Computer Vision algorithms for a day-to-day research activity, our proposed framework has an advantage given by the configurable and scalar architecture. Even if the main focus of the framework is on the Computer Vision processing pipeline, the framework offers solutions to incorporate even more complex activities, such as training Machine Learning models. EECVF aims to become a useful tool for learning activities in the Computer Vision field, as it allows the learner and the teacher to handle only the topics at hand, and not the interconnection necessary for visual processing flow.

scholarly journals Open source computer vision-based layer-wise 3D printing analysis

2020 ◽  
Vol 36 ◽  
pp. 101473 ◽  
Author(s):  
Aliaksei L. Petsiuk ◽  
Joshua M. Pearce
Keyword(s):  
Computer Vision ◽  
3D Printing ◽  
Open Source

Modified Posicast Control Design Method Based on the Parameters of a Fractional Order System

2021 ◽  
Vol 143 (4) ◽  
Author(s):  
Erhan Yumuk ◽  
Müjde Güzelkaya ◽  
İbrahim Eksin
Keyword(s):  
Real Time ◽  
Fractional Order ◽  
Control Method ◽  
Design Method ◽  
Order System ◽  
Half Cycle ◽  
Empirical Formulas ◽  
Real Time System ◽  
Novel Design ◽  
Better Than

Abstract In this study, a novel design method for half-cycle and modified posicast controller structures is proposed for a class of the fractional order systems. In this method, all required design variable values, namely, the input step magnitudes and their application times are obtained as functions of fractional system parameters. Moreover, empirical formulas are obtained for the overshoot values of the compensated system with half-cycle and modified posicast controllers designed utilizing this method. The proposed design methodology has been tested via simulations and ball balancing real-time system. It is observed that the derived formulas are in coherence with outcomes of the simulation and real-time application. Furthermore, the performance of modified posicast controller designed using proposed method is much better than other posicast control method.

Sine-cosine algorithm-based optimization for automatic voltage regulator system

2018 ◽  
Vol 41 (6) ◽  
pp. 1761-1771 ◽  
Author(s):  
Baran Hekimoğlu
Keyword(s):  
Pid Controller ◽  
Design Method ◽  
Voltage Regulator ◽  
Bee Colony ◽  
Automatic Voltage Regulator ◽  
Avr System ◽  
Sine Cosine Algorithm ◽  
Tuning Methods ◽  
Domain Performance ◽  
Novel Design

A novel design method, sine-cosine algorithm (SCA) is presented in this paper to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system. The proposed approach is a simple yet effective algorithm that has balanced exploration and exploitation capabilities to search the solutions space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality tuning of optimum PID controller parameters. The proposed SCA-PID controller is validated by using a time domain performance index. The proposed method was found efficient and robust in improving the transient response of AVR system compared with the PID controllers based on Ziegler-Nichols (ZN), differential evolution (DE), artificial bee colony (ABC) and bio-geography-based optimization (BBO) tuning methods.

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