“Doppler time-of-flight imaging”
Conference:
Type:
Title:
- Doppler time-of-flight imaging
Session/Category Title: Computational Illumination
Presenter(s)/Author(s):
Moderator(s):
Abstract:
Over the last few years, depth cameras have become increasingly popular for a range of applications, including human-computer interaction and gaming, augmented reality, machine vision, and medical imaging. Many of the commercially-available devices use the time-of-flight principle, where active illumination is temporally coded and analyzed in the camera to estimate a per-pixel depth map of the scene. In this paper, we propose a fundamentally new imaging modality for all time-of-flight (ToF) cameras: per-pixel radial velocity measurement. The proposed technique exploits the Doppler effect of objects in motion, which shifts the temporal illumination frequency before it reaches the camera. Using carefully coded illumination and modulation frequencies of the ToF camera, object velocities directly map to measured pixel intensities. We show that a slight modification of our imaging system allows for color, depth, and velocity information to be captured simultaneously. Combining the optical flow computed on the RGB frames with the measured metric radial velocity allows us to further estimate the full 3D metric velocity field of the scene. The proposed technique has applications in many computer graphics and vision problems, for example motion tracking, segmentation, recognition, and motion deblurring.
References:
1. Barron, J., Fleet, D., and Beauchemin, S. 1994. Performance of optical flow techniques. IJCV 12, 1, 43–77. Google ScholarDigital Library
2. Boreman, G. D. 2001. Modulation Transfer Function in Optical and ElectroOptical Systems. SPIE Publications.Google Scholar
3. Büttgen, B., and Seitz, P. 2008. Robust optical time-of-flight range imaging based on smart pixel structures. IEEE Trans. Circuits and Systems 55, 6, 1512–1525.Google ScholarCross Ref
4. Ceperley, P., 2015. Resonances, waves and fields. http://resonanceswavesandfields.blogspot.com/2011/04/28-valid-method-of-multiplying-two.html. {Online; accessed 20-January-2015}.Google Scholar
5. Conroy, R., Dorrington, A., Kunnemeyer, R., and Cree, M. 2009. Range Imager Performance Comparison in Homodyne and Heterodyne Operating Modes. In Proc. SPIE 7239.Google Scholar
6. Doppler, C. J. 1842. Über das farbige Licht der Doppelsterne und einiger anderer Gestirne des Himmels. Abhandlungen der Königl. Böhm. Gesellschaft der Wissenschaften 12, 2, 465–482.Google Scholar
7. Dorrington, A. A., Cree, M. J., Payne, A. D., Conroy, R. M., and Carnegie, D. A. 2007. Achieving sub-millimetre precision with a solid-state full-field heterodyning range imaging camera. In Proc. Meas. Sci. Technol., vol. 18.Google Scholar
8. Erz, M., and Jähne, B. 2009. Radiometric and spectrometric calibrations, and distance noise measurement of ToF cameras. In Dynamic 3D Imaging. Springer, 28–41. Google ScholarDigital Library
9. Gokturk, S., Yalcin, H., and Bamji, C. 2004. A time-of-flight depth sensor – system description, issues and solutions. In Proc. CVPR, 35–35. Google ScholarDigital Library
10. Gu, J., Hitomi, Y., Mitsunaga, T., and Nayar, S. 2010. Coded Rolling Shutter Photography: Flexible Space-Time Sampling. In Proc. ICCP.Google Scholar
11. Gupta, M., Nayar, S. K., Hullin, M., and Martin, J. 2014. Phasor Imaging: A Generalization Of Correlation-Based Time-of-Flight Imaging. Tech. rep., Jun.Google Scholar
12. Heide, F., Hullin, M. B., Gregson, J., and Heidrich, W. 2013. Low-budget transient imaging using photonic mixer devices. ACM Trans. Graph. (SIGGRAPH) 32, 4, 45:1–45:10. Google ScholarDigital Library
13. Heide, F., Xiao, L., Heidrich, W., and Hullin, M. B. 2014. Diffuse mirrors: 3D reconstruction from diffuse indirect illumination using inexpensive time-of-flight sensors. In Proc. CVPR. Google ScholarDigital Library
14. Heide, F., Xiao, L., Kolb, A., Hullin, M. B., and Heidrich, W. 2014. Imaging in scattering media using correlation image sensors and sparse convolutional coding. OSA Opt. Exp. 22, 21, 26338–26350.Google ScholarCross Ref
15. Hoegg, T., Lefloch, D., and Kolb, A. 2013. Real-time Motion Compensation for PMD-ToF Images. In Lecture Notes in Computer Science, vol. 8200.Google Scholar
16. Honegger, D., Meier, L., Tanskanen, P., and Pollefeys, M. 2013. An open source and open hardware embedded metric optical flow CMOS camera for indoor and outdoor applications. In Proc. ICRA, IEEE, 1736–1741.Google Scholar
17. Hontani, H., Oishi, G., and Kitagawa, T. 2014. Local estimation of high velocity optical flow with correlation image sensor. In Proc. ECCV, 235–249.Google Scholar
18. Horn, B., and Schunck, B. 1981. Determining optical flow. Artificial Intelligence 17, 185–203.Google ScholarDigital Library
19. Kadambi, A., Whyte, R., Bhandari, A., Streeter, L., Barsi, C., Dorrington, A., and Raskar, R. 2013. Coded time of flight cameras: sparse deconvolution to address multipath interference and recover time profiles. ACM Trans. Graph. (SIGGRAPH Asia) 32, 6. Google ScholarDigital Library
20. Kirmani, A., Hutchison, T., Davis, J., and Raskar, R. 2009. Looking around the corner using transient imaging. In Proc. ICCV, 159–166.Google Scholar
21. Lange, R., and Seitz, P. 2001. Solid-state time-of-flight range camera. IEEE J. Quantum Electronics 37, 3, 390–397.Google ScholarCross Ref
22. Li, Y., and Stuber, G. 2006. Orthogonal Frequency Division Multiplexing for Wireless Communications. Springer. Google ScholarDigital Library
23. Lindner, M., and Kolb, A. 2006. Lateral and depth calibration of PMD-distance sensors. In Advances in Visual Computing. Springer, 524–533. Google ScholarDigital Library
24. Lindner, M., and Kolb, A. 2009. Compensation of Motion Artifacts for Time-of-Flight Cameras. In Proc. Dynamic 3D Imaging. 16–27. Google ScholarDigital Library
25. Liu, C., Yuen, J., Torralba, A., Sivic, J., and Freeman, W. T. 2008. SIFT flow: Dense correspondence across different scenes. In Computer Vision–ECCV 2008. Springer, 28–42. Google ScholarDigital Library
26. Liu, C. 2009. Beyond pixels: exploring new representations and applications for motion analysis. PhD thesis, MIT. Google ScholarDigital Library
27. Naik, N., Zhao, S., Velten, A., Raskar, R., and Bala, K. 2011. Single view reflectance capture using multiplexed scattering and time-of-flight imaging. ACM Trans. Graph. (SIGGRAPH Asia) 30, 6, 171:1–171:10. Google ScholarDigital Library
28. O’Toole, M., Heide, F., Xiao, L., Hullin, M. B., Heidrich, W., and Kutulakos, K. N. 2014. Temporal frequency probing for 5d transient analysis of global light transport. ACM Trans. Graph. (SIGGRAPH) 33, 4, 87:1–87:11. Google ScholarDigital Library
29. Pandharkar, R., Velten, A., Bardagjy, A., Lawson, E., Bawendi, M., and Raskar, R. 2011. Estimating motion and size of moving non-line-of-sight objects in cluttered environments. In Proc. CVPR, 265–272. Google ScholarDigital Library
30. Tocci, M., Kiser, C., Tocci, N., and Sen, P. 2011. A versatile HDR video production system. ACM Trans. Graph. (SIGGRAPH) 30, 4, 41. Google ScholarDigital Library
31. Velten, A., Willwacher, T., Gupta, O., Veeraraghavan, A., Bawendi, M., and Raskar, R. 2012. Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging. Nat Commun 745, 3.Google Scholar
32. Velten, A., Wu, D., Jarabo, A., Masia, B., Barsi, C., Joshi, C., Lawson, E., Bawendi, M., Gutierrez, D., and Raskar, R. 2013. Femto-photography: Capturing and visualizing the propagation of light. ACM Trans. Graph. (SIGGRAPH) 32, 4, 44:1–44:8. Google ScholarDigital Library
33. Wei, D., Masurel, P., Kurihara, T., and Ando, S. 2006. Optical flow determination with complex-sinusoidally modulated imaging. In Proc. ICSP, vol. 2.Google Scholar
34. Wu, D., Wetzstein, G., Barsi, C., Willwacher, T., O’Toole, M., Naik, N., Dai, Q., Kutulakos, K., and Raskar, R. 2012. Frequency analysis of transient light transport with applications in bare sensor imaging. In Proc. ECCV, 542–555. Google ScholarDigital Library
35. Yasuma, F., Mitsunaga, T., Iso, D., and Nayar, S. K. 2010. Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum. IEEE TIP 19, 9, 2241–2253. Google ScholarDigital Library
