Abstract
Number of mobile devices such as smart phones or Tablet PCs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays which make the interaction with device more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device in the camera’s field of view. In this paper, our gestural interaction heavily relies on particular patterns from local orientation of the image called Rotational Symmetries. This approach is based on finding the most suitable pattern from a large set of rotational symmetries of different orders which ensures a reliable detector for hand gesture. Consequently, gesture detection and tracking can be hired as an efficient tool for 3D manipulation in various applications in computer vision and augmented reality. The final output will be rendered into color anaglyphs for 3D visualization. Depending on the coding technology different low cost 3D glasses will be used for viewers.
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References
Bencheikh, M., Bouzenada, M., Batouche, M.C.: A New Method of Finger Tracking Applied to the Magic Board. In: Conf. on Industrial Technology (2004)
Bretzner, L., Laptev, I., Lindeberg, T.: Hand gesture recognition using multi-scale colour features, hierarchical models and particle filtering. In: Proc. of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, Washington, DC, USA, (2002)
Dorfmueller-Ulhaas, K., Schmalstieg, D.: Finger Tracking for Interaction in Augmented Environments. In: 2nd ACM/IEEE Symposium on Augmented Reality (2001)
Erol, A., Bebis, G., Nicolescu, M., Boyle, R., Twombly, X.: Vision-based hand pose estimation: A review. Computer Vision and Image Understanding, (2007)
Hardenberg, C.V., Berard, B.: Bare-hand human-computer interaction. In: Proceedings of the 2001 Workshop on Perceptive User Interfaces, Orlando, Florida. ACM International Conference Proceeding Series, vol. 15 archive (2001)
Iwai, D., Sato, K.: Heat Sensation in Image Creation with Thermal Vision. In: ACM SIGCHI Int. Conf. on Advances in Computer Entertainment Technology (2005)
Johansson, B.: Low Level Operations and Learning in Computer Vision. Linkoping Studies in Science and Technology Dissertation, Linkopings universitet (2004)
Kolsch, M., Turk, M.: Fast 2D Hand Tracking with Flocks of Features and Multi-Cue Integration. In: Proc. CVPR Workshop (2004)
Fischler, M., Bolles, R.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Readings in Computer Vision: Issues, Problems, Principles, and Paradigms, 726–740 (1987)
Maggioni, C.: A novel gestural input device for virtual reality. In: IEEE Annual International Symposium on Virtual Reality, pp. 118–124 (1993)
Rehg, J., Kanade, T.: Digiteyes Vision-based Human Hand Tracking. Technical Report CMU-CS-TR-93-220, Carnegie Mellon University (1993)
Laptev, I., Lindeberg, T.: Tracking of Multi-state Hand Models Using Particle Filtering and a Hierarchy of Multi-scale Image Features. In: Proc. Scale-Space and Morphology in Computer Vision (1999)
Dubois, E.: A Projection Method To Generate Anaglyph Stereo Images. In: Proc. IEEE Int. Conf. Acoustics Speech Signal Processing (2001)
Jones, G., Lee, D., Holliman, N., Ezra, D.: Controlling Perceived Depth in Stereoscopic Images. Stereoscopic Displays and Virtual Reality Systems VIII (2001)
Zhou, H., Ruan, Q.: Finger Countour Tracking Based on Model. In: Conf. on Computers, Comunications, Control and Power Engineering (2002)
Lowe, D.: Distinctive image features from scale-invariant keypoints. IJCV (2004)
Hartley, R., Zisserman, A.: Multiple View Geometry. Cambridge University Press, Cambridge (2004)
Holliman, N.: Mapping perceived depth to regions of interest in stereoscopic images. In: Proc. SPIE, Stereoscopic Displays and Virtual Reality Systems XI (2004)
Tran, V. M.: New methods for rendering of anaglyph stereoscopic images on CRT displays and photo-quality ink-jet printers. Ottawa-Carleton Institute for Electrical and Computer Engineering, SITE (2005)
Stenger, B., Thayananthan, A., Torr, P., Cipolla, R.: Model-based hand tracking using a hierarchical Bayesian filter. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(9), 1372–1384 (2006)
Yang, R., Sarkar, S.: Gesture Recognition using Hidden Markov Models from Fragmented Observations. In: Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2006)
Mcallister, D.F., Zhou, Y., Sullivan, S.: Methods for computing color anaglyphs (2010)
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Yousefi, S., Kondori, F.A., Li, H. (2011). 3D Gestural Interaction for Stereoscopic Visualization on Mobile Devices. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds) Computer Analysis of Images and Patterns. CAIP 2011. Lecture Notes in Computer Science, vol 6855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23678-5_66
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DOI: https://doi.org/10.1007/978-3-642-23678-5_66
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