Abstract
As technology advances and better virtual interfaces emerge, there is a demand for new kinds of interaction devices. The currently being used devices like keyboard, mouse, pens, etc. have been the most popular among these virtual interfaces. With the advancement of technology where speech and gestures have become the key components to interact with smart devices a replacement for currently used devices is needed. The development of user interfaces influences the changes in Human-Computer Interaction (HCI). This paper focuses to design an input device using computer vision and gesture recognition techniques. This device interacts with a computer using hand gestures, providing an intuitive cost-effective way of performing mouse controls. Various algorithms and techniques are used to make the product user-friendly. We have designed a colored glove that can work in various environments and control the navigation along with functions of the mouse such as left-click, right-click, dragging, and scrolling swiftly. This real-time application allows for practical interaction between users and the system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jenny, P., et al.: Human-Computer Interaction. Addison-Wesley Longman Ltd. (1994)
Lenman, et al.: Computer vision based hand gesture interfaces for human-computer interaction. RIT, Sweden (2002)
Mitra, et al.: Gesture recognition: a survey. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 37(3), 311–324 (2007)
Smith, et al.: Hand gesture recognition system and method. U.S. Patent No. 6,128,003, 3 October 2000
Vincze, et al.: Hand gestures mouse cursor control. Sci. Bull. “Petru Maior” Univ. Tg. Mures 11, 46–49 (2014)
Aurich, et al.: Non-linear Gaussian filters performing edge preserving diffusion. In: Mustererkennung 1995, pp. 538–545. Springer, Heidelberg (1995)
Gil, et al.: Efficient dilation, erosion, opening, and closing algorithms. IEEE Trans. PAMI 24(12), 1606–1617 (2002)
Grif, et al.: Mouse cursor control system based on hand gesture. Procedia Technol. 22, 657–661 (2016)
Meena, et al.: A study on hand gesture recognition technique. Dissertation (2011)
Hernando, G., et al.: First-person hand action benchmark with RGB-D videos and 3D hand pose annotations. In: Proceedings of the IEEE Conference on CVPR (2018)
Wang, et al.: Real-time hand-tracking with a color glove. ACM Trans. Graph. (TOG) 28(3), 63 (2009)
Dadashzadeh, et al.: HGR-Net: a fusion network for hand gesture segmentation and recognition. arXiv preprint arXiv:1806.05653 (2018)
Gu, Y., et al.: Human gesture recognition through a Kinect sensor. In: 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE (2012)
Shao, L.: Hand movement and gesture recognition using Leap Motion Controller. Virtual Reality, Course Report (2016)
Sharp, et al.: Accurate, robust, and flexible real-time hand tracking. In: Proceedings of the 33rd Annual ACM ACI. ACM (2015)
Meyer, et al.: Color image segmentation. In: 1992 International Conference on Image Processing and its Applications. IET (1992)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Pundir, P., Agarwal, A., Kumar, K. (2021). Swift Controller: A Computer Vision Based Mouse Controller. In: Tripathi, M., Upadhyaya, S. (eds) Conference Proceedings of ICDLAIR2019. ICDLAIR 2019. Lecture Notes in Networks and Systems, vol 175. Springer, Cham. https://doi.org/10.1007/978-3-030-67187-7_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-67187-7_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-67186-0
Online ISBN: 978-3-030-67187-7
eBook Packages: EngineeringEngineering (R0)