Search Results for « Gesture-based »

Abstract In Australian Indigenous societies the means for demonstrating kinship-based respect are rich and varied, and mastery of their ideological and contextual dimensions is highly valued and an indication of communicative expertise. Special speech registers, sometimes referred to as ‘mother-in-law’, ‘brother-in-law’, or ‘avoidance’ languages, are one aspect of this complexity. Another dimension of respect is afforded by Australian Indigenous sign languages, used in contexts where speech itself is disallowed as well as in everyday interactions where signing is practical and useful. What is lacking from the majority of accounts of these special semiotic repertoires is an investigation of the ways that speech and communicative actions, such as sign or gesture, may work together in such contexts. Also neglected is the possibility that the articulation of signs and gestures may be modified to indicate a respectful stance towards avoided kin. Drawing on both archival sources and recent fieldwork, this paper delineates some of the articulatory dimensions of signs and gestures used in this domain.

The focus of this paper is on a gesture-based interface designed for controlling a mobile robot equipped with a manipulator. This interface employs a camera to track a person's movements and recognize gestures that involve arm motion. To enable the robot to follow a person reliably through environments with changing lighting conditions, a fast, adaptive tracking algorithm is utilized. The paper compares two alternative approaches for gesture recognition: a template-based approach and a neural network approach. Both methods are combined with the Viterbi algorithm to recognize arm motion-based gestures in addition to static arm poses. The results of this study are presented in the context of an interactive clean-up task, where a person directs the robot to specific locations that require cleaning and instructs it to pick up trash. Service robotics is currently an important area of research, with significant potential for societal impact. As service robots interact directly with people, developing intuitive and user-friendly interfaces is crucial. While prior work has primarily focused on navigation and manipulation, few robotic systems possess flexible user interfaces that enable natural and easy-to-use control of the robot.

Recent advancements in gesture detection and hand tracking have created both significant opportunities and challenges in the field of virtual reality (VR) and user interaction. With the increased focus on reducing physical interactions due to the COVID-19 pandemic, the need for alternative, non-contact methods of computer operation has grown [15]. These innovations hold the potential to reduce reliance on traditional input devices like keyboards and mice, fostering a more immersive and intuitive user experience. One exciting direction for future development is the ability to perform complex tasks, such as clicking, dragging objects and controlling purely through hand gestures. This could open up new possibilities for VR environments, where users can interact naturally with digital objects. The key advantage of such an input method is that it requires only a camera, making it accessible and adaptable to various settings without the need for additional hardware. In the future, gesture recognition may become an essential part of our interaction with technology, leading to seamless and efficient virtual experiences. The proposed project, leveraging Python and OpenCV for gesture recognition, seeks to explore these possibilities and inspire further research in this field.