Recommandé
Recommandé
Contenu connexe
Tendances
Tendances (17)
Similaire à Interactive Wall (Multi Touch Interactive Surface)
Similaire à Interactive Wall (Multi Touch Interactive Surface) (20)
Dernier
Dernier (20)
Interactive Wall (Multi Touch Interactive Surface)
- 1. Multi-touch Interactive Surface Supervisors: Professor Dr. Mohammed Roushdy Dr. Haythem El-Messiry T.A. Ahmad Salah 1
- 3. Agenda Introduction Physical Environment and Framework Project Modules and Applications Challenges Conclusion and Future work Tools and References 3
- 5. Current Multi-touch devices are:Expensive Heavy Fragile Consume space 4
- 7. Generic Framework for Human Computer Interaction (HCI) using hand gestures.6
- 8. Physical Environment Physical environment consists of: A projector. A webcam placed over the projector’s lens capturing the projected surface. 7
- 9. 1.25 m 0.8 m 8
- 10. Physical Environment Surface 2.15 m Camera Projector 9
- 11. Framework 10 Controller Configuration Module Input Module Hand Tracking Hand Segmentation Hand gesture Recognition Interface
- 13. Detect Corners Controller Module Color Mapping Search for hand in entry point Segmentation Construct the search window Track the hand Fire Event Gesture Recognition 12
- 16. A set of colors are projected and captured for the color calibration process.Desktop Colors Projected Colors 14
- 18. Input Module 16
- 20. Hand Tracking Module 18
- 23. Hand Segmentation Module 20
- 26. Convert colors of the desktop image to that of the captured image.22
- 28. Calculate the transformation matrix A for each region.
- 29. b=A * x ; where b is the calibrated color, A is the transformation matrix, x the desktop color.23
- 30. Segmentation Results Largest Blob Extraction Desktop Captured Segmented Global thresholding 24
- 32. A bounding box (60 * 60) is constructed around the largest blob.Original Closed Original - Closed
- 33. Hand Gesture Recognition Module 26
- 34. Hand Gesture Recognition 27 Contour Tracing Contour Re-sampling EFD DB EFD Gesture Type
- 39. The interface handles the raised events.
- 40. The user can map the gestures to events.32
- 41. Main Gestures 33
- 42. Applications Puzzle game 34 Painter Image Viewer
- 43. Demo 35
- 46. Image processing can be very powerful if used in the appropriate environment.37
- 48. Multi hands’ and multi users’ interaction.
- 49. Interactive Wall can be used with another surface other than the projector, for example a large screen can be used.
- 52. MatLab
- 54. Projector39
- 56. AsanterabiMalima, ErolÖzgür, and MüjdatÇetin, A Fast algorithm for vision-based hand gesture recognition robot control, Faculty of Engineering and Natural Science, Sabancı University, Tuzla, İstanbul, Turkey, 2006.40
- 61. NgonT.Truong, Jae-GyunGwag, Yong-Jin Park, and Suk-Ha Lee, Genetic Diversity of Soybean Pod Shape Based on Elliptical Fourier Descriptors, Dep. of Plant Science, Seoul National University, Seoul 151-742, Korea Dep. Of Crop Sciences, Can Tho University, Can Tho, Viet Nam Genetic Resources Div., National Institute of Agricultural Biotechnology, Suwon 441-707, Korea, 2005.
- 64. Stephen Wolf,Color Correction Matrix for Digital Still and Video Imaging Systems, U.S. DEPARTMENT OF COMMERCE, December 2003.
- 65. Qing Chen, Evaluation of OCR Algorithms for Images with Different Spatial Resolutions and Noises, School of Information Technology and Engineering Faculty of Engineering University of Ottawa ©, Ottawa, Canada, 2003.
- 67. Dengsheng Zhang and Guojun Lu,A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures, Gippsland School of Computing and Information Technology Monash University Churchill, Victoria 3842, Australia, 2001.43
- 69. Kenny Teng, Jeremy Ng, Shirlene Lim, Computer Vision Based Sign Language Recognition for Numbers.
- 71. A. M. Hamad, Fawziashaaban, Mona Gabr, NohaSayed, RababHussien, Robot Vision, Faculty of computer and Information Sciences Ain Shams University, Cairo, Egypt, 2008.44
- 72. Thank You ! 45
Notes de l'éditeur
- Our goal is the development of a more natural interface; a camera-projector system using hand gesture analysis.Optical cameraProjector Framework Hand gesture , ApplicationsA development framework that gives any application using it the ability to allow the user to interact with this application using “Hand Gestures”.A stream of video is captured using low cost webcam then processed in the framework to extract the hand position, recognize the gesture and finally the application handles the fired events.
- Our goal is the development of a more natural interface; a camera-projector system using hand gesture analysis.Optical cameraProjector Framework Hand gesture , ApplicationsA development framework that gives any application using it the ability to allow the user to interact with this application using “Hand Gestures”.A stream of video is captured using low cost webcam then processed in the framework to extract the hand position, recognize the gesture and finally the application handles the fired events.
- 1. Initialization (k=0). In this step it is looked for the object in the whole image due we do not know previously the object position. We obtain this way. Also we can considerer initially a big error tolerance.2. Prediction (k>0). In this stage using the Kalman filter we predict the relative position of the object, such position is considered as search center to find the object.3. Correction (k>0). In this part we locate the object (which is in the neighborhood point predicted in the previous stage) and we use its realposition (measurement) to carry out the state correction using the Kalman filter finding this way .The steps 2 and 3 are carried out while the object tracking runs.the equations for the Kalman filter fall into two groups: Time update equations and measurement update equations. The time update equations are responsible for projecting forward (in time) the current state and error covarianceestimates to obtain the a priori estimates for the next time step. The measurement update equations are responsible for the feedback—i.e. for incorporating a new measurement intothe a priori estimate to obtain an improved a posteriori estimate.
- Change images