Virtual mouse
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The document describes a proposed virtual mouse system that uses hand gesture recognition instead of a physical mouse. It discusses the limitations of existing input devices like trackballs and optical mice. The proposed system uses a webcam to capture images of hand gestures, applies object recognition techniques to identify gestures, and translates the gestures to mouse events on the screen. It outlines the hardware and software requirements and modules needed to implement the virtual mouse, including image acquisition, object recognition, coordinate calculation, and event generation. Work done so far includes literature research and initial implementation efforts.
Virtual mouse
- 1. VIRTUAL MOUSE Nikhil Mane -100731 Saurabh Shigwan -100753 Noel Francis -100674 Group- 17
- 2. • An Introduction • Why Virtual Mouse is Needed • Existing System • Proposed System • Flow Charts • Hardware and Software Requirements • Work Done • Conclusion References Table of Contents
- 3. • “Your mouse has moved. Windows must be restarted for the change to take effect.” <click on OK to continue>
- 4. SPATIAL – An Introduction • There is no other more popular navigation/interaction device than the mouse. • Overcoming the restrictions a corporeal device has would enrich the experience of interaction. • Keeping this in mind, we present an idea of implementing a virtual mouse system as an alternative. Virtual Mouse is: • User makes a specified hand gesture that is captured by a camera. • Object recognition techniques are used to extract information from the capture. • This is then translated to some meaningful event on the screen. An Introduction
- 5. Why VIRTUAL MOUSE is Needed • Mouse is a physical device subject to mechanical wear and tear. • It is not easy to adapt to different environments and is often limited by environment. • Limited functions even in present operational environments. • VIRTUAL MOUSE hopes to fulfill these requirements of the user by overcoming normal physical barriers.
- 6. Existing System TrackBall: • The user rolls the ball with the thumb, fingers, or the palm of the hand to move a cursor. • Large tracker balls are common on CAD workstations for easy precision. • Before the advent of the touchpad, small trackballs were common on portable computers. Disadvantages • Usually not as accurate as a mouse. • Ball mechanism of trackballs requires more frequent cleaning than a mouse. • Not very user friendly.
- 7. Existing System(continued) Mechanical Mouse : • A single ball that could rotate in any direction. • As part of the hardware package of the Xerox Alto computer. • Detection of the motion of the ball was light based with the help of chopper wheels. Disadvantages • Cannot provide high precision performance. • Has specific surface requirements to operate. • Needs more desk space when compared with a trackball.
- 8. Existing System(continued) Optical Mouse : • Uses a light-emitting diode and photodiodes to detect movement relative to the underlying surface. • Digital image correlation, a technology pioneered by the defense industry for tracking military targets. • Use image sensors to image naturally occurring texture in materials such as wood, cloth, mouse pads and • Image captures in continuous succession and comparison to determine mouse movement. Disadvantages • Special hardware required. • Again, specific surface requirements.
- 9. Proposed System Features of VIRTUAL MOUSE: • Any new product should either make human life more comfortable, more productive or more fun. • Provides greater flexibility than the existing system. • Can provide more functions depending on the choice of object. • Easy to modify and adapt • Less prone to physical damage due to absence of a fixed physical device. • Avoid the mouse-related wrist damage like CTS & RSI. • Also, there is a certain degree of fun & entertainment associated with the whole idea.
- 10. Proposed System(continued) It is divided into the following modules: • Module 1 (Image Acquisition). • Module 2 (Object Recognition). • Module 3 (Object Tracing and Information Retrieval). • Module 4 (Point Coordinate Calculation and Motion Analysis). • Module 5 (Setting Cursor Position) • Module 6 (Event Generation)
- 12. Flow charts (continued) Camera Capture Module Mouse Driver Module Camera Capture Module Image Acquisition Object Recognition Trace Object Coordinate calculation Mouse Driver Module Setting Cursor Position Event Generation
- 13. Final Flow chart Image Acquisition Object Recognition Trace Object Coordinate calculation Setting Cursor Position Event Generation
- 14. Hardware and Software Requirements Hardware Requirements- • Intel Pentium D processor 1.8 GHz or AMD Athlon X2 processor 1.8 GHz or higher • 3 GB RAM • 5 GB HDD space • Peripheral webcam at least 30 frames/second, 640x480 resolution Software Requirements- • Windows XP x86 or higher (for x86 environment) • Windows XP professional x64 or higher (for x64 environment) • .NET framework 3.5 or higher • Visual Studio 2008 professional • EmguCV library (wrapper of OpenCV library for .NET framework) • EmguCV library 64 bit binaries (for developing on x64 environment) • Webcam drivers (device specific)
- 15. Work Done • Studied the existing systems and available information to understand. • Hence, proposed a new system. • Main purpose – to eliminate physical constraints and add adaptability. • A literature survey in relation to the various contexts was done. • Implementation work has been started. • VM
- 16. Conclusion • VIRTUAL MOUSE is an idea of implementing an adaptable, multi- functional navigation/interaction tool that overcomes physical barriers. • The system will be ‘real’ enough to not affect the interaction much. • Ease of use is the foremost concern. • Availability, Adaptability and Ability • Project goal will be to build a system that satisfies all three ideals Future Enhancement : • Development for specific objects. • Creation of particular action areas for utility. • More advanced and highly specific functionality.
- 17. References • 1. Richard E. Woods, Rafael C. Gonzalez, “Digital Image Processing”, Pearson Education Asia, 3/E, 2008 • 2. Ming-Hsuan Yang, Narendra Ahuja, “Face detection and gesture recognition for human- computer interaction” O’Reilly, 2006. • 3. Gary Bradski, Adrian Kaehler, “Learning OpenCV: Computer Vision with the OpenCV Library”, Shroff/O'Reilly, 2008 • 4. Stanley B. Lippman, Josee Lajoie, “A C++ Primer”, Addison-Wesley, 3rd Edition 2008 • 5. Ivor Horton, “Ivor Horton's Beginning Visual C++ 2008”, Wiley India Pvt. Ltd/Wrox, 2008 • 6. Jon Skeet, “C# in Depth”, Manning Publication, Second Edition, 2008 • 7. Kogent Solutions Inc. , “.NET 3.5 Programming Black Book: Covering .NET Framework, VB 2008, C# 2008, And ASP.NET 3.5” , Wiley India Pvt. Ltd, 2010 • 8. Christian Nagel, Bill Evjan, Jay Glynn, Morgan Skinner, Karli Watson, “Professional C# 2008”, Wiley, 2008 • 9. Chensheng Wang, Fei Wang “A Knowledge-based Strategy for Object Recognition and Reconstruction”, 2009 • 10. Soo Chahn Lee, Duck Hoon Kim, IlDongYun andSangUk Lee School of EECS, “How Can We Evaluate Object Recognition Algorithms” ,IEEE, 25 June 2005 • 11. M. A. Moni, A B M Shawkat Ali, “HMM based Hand Gesture Recognition: A Review on Techniques and Approaches”, IEEE, 03 January 2006 • 12. Jacinto Nascimento, Jorge S. Marques,”New Performance Evaluation Metrics for Object Detection Algorithms”, ISR/IST, 2006. • 13. http://opencv.willowgarage.com/wiki/ • 14. http://en.wikipedia.org/wiki/OpenCV’ • 15. http://www.emgu.com/wiki/index.php/OpenCV • 16. http://www.cs.iit.edu/~agam/cs512/lect-notes/opencv-intro/opencv-intro.html • 17. http://msdn.microsoft.com/en-us/library/aa139615.aspx • 18. http://www.youtube.com/user/badrepent • 19. http://stackoverflow.com/questions/3652327/choice-between-win32-apis-and-net-framework • 20. http://stackoverflow.com/questions/3762081/using-c-for-real-time-applications • 21. http://stackoverflow.com/questions/3691198/selecting-an-appropriate-ide 22. http://note.sonots.com/SciSoftware/haartraining.html •