This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Motion Field Estimation from Alternate Exposure Images
August 2011 (vol. 33 no. 8)
pp. 1577-1589
ASCII Text
x 
 
Anita Sellent, Martin Eisemann, Bastian Goldlücke, Daniel Cremers, Marcus Magnor, "Motion Field Estimation from Alternate Exposure Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 8, pp. 1577-1589, August, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2010.218,
author = {Anita Sellent and Martin Eisemann and Bastian Goldlücke and Daniel Cremers and Marcus Magnor},
title = {Motion Field Estimation from Alternate Exposure Images},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {33},
number = {8},
issn = {0162-8828},
year = {2011},
pages = {1577-1589},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.218},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Motion Field Estimation from Alternate Exposure Images
IS - 8
SN - 0162-8828
SP1577
EP1589
EPD - 1577-1589
A1 - Anita Sellent,
A1 - Martin Eisemann,
A1 - Bastian Goldlücke,
A1 - Daniel Cremers,
A1 - Marcus Magnor,
PY - 2011
KW - Motion field estimation
KW - motion blur
KW - optical flow
KW - occlusion
KW - computational video.
VL - 33
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Anita Sellent, TU Braunschweig, Braunschweig
Martin Eisemann, TU Braunschweig, Braunschweig
Bastian Goldlücke, TU Munich, Munich
Daniel Cremers, TU Munich, Munich
Marcus Magnor, TU Braunschweig, Braunschweig
Traditional optical flow algorithms rely on consecutive short-exposed images. In this work, we make use of an additional long-exposed image for motion field estimation. Long-exposed images integrate motion information directly in the form of motion-blur. With this additional information, more robust and accurate motion fields can be estimated. In addition, the moment of occlusion can be determined. Considering the basic signal-theoretical problem in motion field estimation, we exploit the fact that long-exposed images integrate motion information to prevent temporal aliasing. A suitable image formation model relates the long-exposed image to preceding and succeeding short-exposed images in terms of dense 2D motion and per-pixel occlusion/disocclusion timings. Based on our image formation model, we describe a practical variational algorithm to estimate the motion field not only for visible image regions but also for regions getting occluded. Results for synthetic as well as real-world scenes demonstrate the validity of the approach.

[1] W. Christmas, "Filtering Requirements for Gradient-Based Optical Flow Measurement," IEEE Trans. Image Processing, vol. 9, no. 10, pp. 1817-1820, Oct. 2000.
[2] T. Brox, A. Bruhn, N. Papenberg, and J. Weickert, "High Accuracy Optical Flow Estimation Based on a Theory for Warping," Proc. European Conf. Computer Vision, pp. 25-36, 2004.
[3] L. Alvarez, R. Deriche, T. Papadopoulo, and J. Sanchez, "Symmetrical Dense Optical Flow Estimation with Occlusions Detection," Int'l J. Computer Vision, vol. 75, no. 3, pp. 371-385, 2007.
[4] J. Xiao, H. Cheng, H. Sawhney, C. Rao, and M. Isnardi, "Bilateral Filtering-Based Optical Flow Estimation with Occlusion Detection," Proc. European Conf. Computer Vision, pp. 211-224, 2006.
[5] A. Sellent, M. Eisemann, and M. Magnor, "Motion Field and Occlusion Time Estimation via Alternate Exposure Flow," Proc. IEEE Int'l Conf. Computational Photography, Apr. 2009.
[6] A. Sellent, M. Eisemann, B. Goldlücke, T. Pock, D. Cremers, and M. Magnor, "Variational Optical Flow from Alternate Exposure Images," Proc. Vision Modeling and Visualization Workshop '09, pp. 135-143, Nov. 2009.
[7] J. Aggarwal and N. Nandhakumar, "On the Computation of Motion from Sequences of Images—A Review," Proc. IEEE, vol. 76, no. 8, pp. 917-935, Aug. 1988.
[8] J. Barron, D. Fleet, and S. Beauchemin, "Performance of Optical Flow Techniques," Int'l J. Computer Vision, vol. 12, no. 1, pp. 43-77, 1994.
[9] A. Mitiche and P. Bouthemy, "Computation and Analysis of Image Motion: A Synopsis of Current Problems and Methods," Int'l J. Computer Vision, vol. 19, no. 1, pp. 29-55, 1996.
[10] P. Sand and S. Teller, "Particle Video: Long-Range Motion Estimation Using Point Trajectories," Int'l J. Computer Vision, vol. 80, no. 1, pp. 72-91, 2008.
[11] S. Lim, J. Apostolopoulos, and A. Gamal, "Optical Flow Estimation Using Temporally Oversampled Video," IEEE Trans. Information Processing, vol. 14, no. 8, pp. 1074-1087, Aug. 2005.
[12] D. Mahajan, F. Huang, W. Matusik, R. Ramamoorthi, and P. Belhumeur, "Moving Gradients: A Path-Based Method for Plausible Image Interpolation," ACM Trans. Graphics, vol. 28, no. 3, p. 42, 2009.
[13] I.M. Rekleitis, "Optical Flow Recognition from the Power Spectrum of a Single Blurred Image," Proc. Int'l Conf. Image Processing, pp. 791-794, 1996.
[14] T. Pao and M. Kuo, "Estimation of the Point Spread Function of a Motion-Blurred Object from Autocorrelation," Proc. SPIE, 2003.
[15] S. Dai and Y. Wu, "Motion from Blur," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
[16] R. Fergus, B. Singh, A. Hertzmann, S. Roweis, and W. Freeman, "Removing Camera Shake from a Single Photograph," Proc. SIGGRAPH, pp. 787-794, 2006.
[17] J. Jia, "Single Image Motion Deblurring Using Transparency," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2007.
[18] D. Kundur and D. Hatzinakos, "Blind Image Deconvolution," IEEE Signal Processing Magazine, vol. 13, no. 3, pp. 43-64, May 1996.
[19] A. Levin, "Blind Motion Deblurring Using Image Statistics," Advances in Neural Information Processing Systems, vol. 19, pp. 841-848, MIT Press, 2007.
[20] L. Yuan, J. Sun, L. Quan, and H.-Y. Shum, "Image Deblurring with Blurred/Noisy Image Pairs," Proc. SIGGRAPH, no. 3, 2007.
[21] M. Ben-Ezra and S.K. Nayar, "Motion Deblurring Using Hybrid Imaging," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 657-664, 2003.
[22] Y. Tai, H. Du, M. Brown, and S. Lin, "Image/Video Deblurring Using a Hybrid Camera," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
[23] W.-G. Chen, N. Nandhakumar, and W.N. Martin, "Image Motion Estimation from Motion Smear—A New Computational Model," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 4, pp. 412-425, Apr. 1996.
[24] W.-G. Chen, N. Nandhakumar, and W.N. Martin, "Estimating Image Motion from Smear: A Sensor System and Extensions," Proc. Int'l Conf. Image Processing, pp. 199-202, 1995.
[25] L. Bar, B. Berkels, M. Rumpf, and G. Sapiro, "A Variational Framework for Simultaneous Motion Estimation and Restoration of Motion-Blurred Video," Proc. IEEE Int'l Conf. Computer Vision, pp. 1-8, 2007.
[26] A. Agrawal, Y. Xu, and R. Raskar, "Invertible Motion Blur in Video," ACM Trans. Graphics, vol. 28, no. 3, pp. 1-8, 2009.
[27] P. Favaro and S. Soatto, "A Variational Approach to Scene Reconstruction and Image Segmentation from Motion-Blur Cues," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2004.
[28] C. Zach, T. Pock, and H. Bischof, "A Duality Based Approach for Realtime TV-$L^1$ Optical Flow," Proc. Symp. German Assoc. Pattern Recognition, vol. 4713, pp. 214-223, 2007.
[29] S. Baker, D. Scharstein, J. Lewis, S. Roth, M. Black, and R. Szeliski, "A Database and Evaluation Methodology for Optical Flow," Proc. IEEE Int'l Conf. Computer Vision, 2007.
[30] A. Chambolle, "An Algorithm for Total Variation Minimization and Applications," J. Math. Imaging and Vision, vol. 20, no. 1, pp. 89-97, 2004.

Index Terms:
Motion field estimation, motion blur, optical flow, occlusion, computational video.
Citation:
Anita Sellent, Martin Eisemann, Bastian Goldlücke, Daniel Cremers, Marcus Magnor, "Motion Field Estimation from Alternate Exposure Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 8, pp. 1577-1589, Aug. 2011, doi:10.1109/TPAMI.2010.218
Usage of this product signifies your acceptance of the Terms of Use.