Abstract
Images projected on to a planar projection surface undergoes keystone distortion when projector is not perpendicular to projection surface. Further in the case of handheld projector, the projected image does not remain steady on the surface due to shaky movements of the hand. This paper introduces a simple approach to stabilise such shaking images using an additional inertial measurement unit (IMU) consisting of gyroscope and accelerometer sensors attached into handheld projector. The approach explicitly estimates the transformation between projector plane and projection surface through out the perturbation of projector, which is used for calculating the prewarped image. Attached IMU gives the rotation angles along all 3 axes. These angles are used in estimating the prewarping transformation. A novel approach has been presented for solving the stabilization problem for a shaking projector in both calibrated and uncalibrated setting. We demonstrate the effectiveness of this approach in getting a stabilized and keystone corrected image on a planar surface continuously with good accuracy in real time compared to existing methods.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Woodman, O.J.: An introduction to inertial navigation. University of Cambridge, Computer Laboratory, Technical report UCAMCL-TR-696 14, 15 (2007)
Sukthankar, R., Stockton, R.G., Mullin, M.D.: Smarter presentations: exploiting homography in camera-projector systems. In: Proceedings of the Eighth IEEE International Conference on Computer Vision, ICCV 2001, vol. 1, pp. 247–253. IEEE (2001)
Li, B., Sezan, I.: Automatic keystone correction for smart projectors with embedded camera. In: 2004 International Conference on Image Processing, ICIP 2004, vol. 4, pp. 2829–2832. IEEE (2004)
Li, Z., Wong, K.H., Gong, Y., Chang, M.Y.: An effective method for movable projector keystone correction. IEEE Trans. Multimedia 13, 155–160 (2011)
Raskar, R., Beardsley, P.: A self-correcting projector. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 2, pp. II–504. IEEE (2001)
Steiger, A., Hein, B., Wörn, H.: A real-timewearable projector-wiimote-system for augmented reality interaction scenarios on plane objects. In: 2010 41st International Symposium on Robotics (ISR) and 2010 6th German Conference on Robotics (ROBOTIK), pp. 1–6. VDE (2010)
Xu, W., Wang, Y., Liu, Y., Weng, D., Tan, M., Salzmann, M.: Real-time keystone correction for hand-held projectors with an RGBD camera. In: ICIP, pp. 3142–3146 (2013)
Min, H.G., Jeung, E.T.: Complementary filter design for angle estimation using mems accelerometer and gyroscope, pp. 641–773. Department of Control and Instrumentation, Changwon National University, Changwon, Korea (2015)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2003)
Mair, E., Fleps, M., Suppa, M., Burschka, D.: Spatio-temporal initialization for IMU to camera registration. In: 2011 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 557–564. IEEE (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Bhargava, M., Ramakrishnan, K. (2016). Joint Keystone Correction and Shake Removal for a Hand Held Projector. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10073. Springer, Cham. https://doi.org/10.1007/978-3-319-50832-0_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-50832-0_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-50831-3
Online ISBN: 978-3-319-50832-0
eBook Packages: Computer ScienceComputer Science (R0)