OpenMG: An Open-Source Middleware Interface for Gesture Recognition

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.

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Hand Gesture Recognition to Implement Virtual Mouse Using Open Source Computer Vision Library: Python

Learning and Analytics in Intelligent Systems - Proceedings of International Conference on Advances in Computer Engineering and Communication Systems ◽

10.1007/978-981-15-9293-5_39 ◽

2021 ◽

pp. 435-446

Author(s):

Gummadi Sai Mahitha ◽

Banala Revanth ◽

Gaddam Geetha ◽

Ramavath Sirisha

Keyword(s):

Computer Vision ◽

Open Source ◽

Gesture Recognition ◽

Hand Gesture Recognition ◽

Hand Gesture ◽

Virtual Mouse

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Sparsh UI: A Multi-Touch Framework for Collaboration and Modular Gesture Recognition

ASME-AFM 2009 World Conference on Innovative Virtual Reality ◽

10.1115/winvr2009-740 ◽

2009 ◽

Cited By ~ 4

Author(s):

Prasad Ramanahally ◽

Stephen Gilbert ◽

Thomas Niedzielski ◽

Desire´e Vela´zquez ◽

Cole Anagnost

Keyword(s):

Rapid Prototyping ◽

Open Source ◽

Programming Language ◽

Gesture Recognition ◽

Virtual Assembly ◽

Touch Input ◽

Cross Platform

Most current multi-touch libraries provide support to recognize the touch input from particular hardware and seldom support complex gestures. For rapid prototyping and development of multi-touch applications, particularly for collaboration across multiple disparate devices, there is a need for a framework which can support an array of multi-touch hardware, provide gesture processing, be cross platform compatible, and allow applications to be developed in the desired programming language. In this paper we present criteria for evaluating a multi-touch library and “Sparsh UI”— an open source multi-touch library which is a novel attempt to address these issues by enabling developers to easily develop multi-touch applications. We also compare Sparsh UI with other multi-touch libraries and describe several Sparsh-based applications, including BasePlate, a system for collaborative virtual assembly.

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