Abstract
During the last years, Time-of-Flight sensors achieved a significant impact onto research fields in computer vision. For dynamic scenes however, most sensor’s working principles lead to significant artifacts in respect to sensor or object motion – artifacts that commonly affect distance reliability and thus affect downstream processing tasks in a negative way.
We therefore introduce a compensation approach for sensors based on the Photonic Mixing Device (PMD). Out technique deals with both, lateral and axial motion artifacts. The lateral compensation tracks object motion on the level of phase images and accordingly adjusts the depth image computation in order to reduce artifacts and enhances depth reliability. The axial motion compensation is based on an axial motion estimation and a theoretical model for axial motion deviation errors. Both components utilize fast optical flow algorithms.
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References
PMD Technologies, http://pmdtec.com
Kraft, H., Frey, J., Moeller, T., Albrecht, M., Grothof, M., Schink, B., Hess, H., Buxbaum, B.: 3D-camera of high 3D-frame rate, depth-resolution and background light elimination based on improved PMD (photonic mixer device)-technologies. In: OPTO (2004)
Lange, R.: 3D time-of-flight Distance Measurement with Custom Solid-State Image Sensors in CMOS/CCD-Technology. PhD thesis, University of Siegen (2000)
Xu, Z., Schwarte, R., Heinol, H., Buxbaum, B., Ringbeck, T.: Smart pixel – photonic mixer device (PMD). In: Proc. Int. Conf. on Mechatron. & Machine Vision, pp. 259–264 (1998)
Kolb, A., Barth, E., Koch, R., Larsen, R.: Time-of-flight sensors in computer graphics. In: Proc. Eurographics (State-of-the-Art Report) (2009)
Schmidt, M.: Spatiotemporal Analysis of Imagery. PhD thesis, University of Heidelberg (2008)
Lottner, O., Sluiter, A., Hartmann, K., Weihs, W.: Movement artefacts in range images of time-of-flight cameras. In: International Symposium on Signals, Circuits & Systems - ISSCS 2007, vol. 2, pp. 117–120 (2007)
Horn, B., Schunck, B.: Determining Optical Flow. Jones and Bartlett Publishers, Inc. (1992)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of the 7th International Joint Conference on Artificial Intelligence (IJCAI 1981), pp. 674–679 (1981)
Sturmer, M., Penne, J., Hornegger, J.: Standardization of intensity-values acquired by time-of-flight-cameras. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008. CVPRW 2008, pp. 1–6 (2008)
Zach, C., Pock, T., Bischof, H.: A duality based approach for realtime tv-l1 optical flow. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 214–223. Springer, Heidelberg (2007)
Middlebury Database: http://vision.middlebury.edu/flow/
Lindner, M., Kolb, A.: Lateral and depth calibration of PMD-distance sensors. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Nefian, A., Meenakshisundaram, G., Pascucci, V., Zara, J., Molineros, J., Theisel, H., Malzbender, T. (eds.) ISVC 2006. LNCS, vol. 4292, pp. 524–533. Springer, Heidelberg (2006)
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Lindner, M., Kolb, A. (2009). Compensation of Motion Artifacts for Time-of-Flight Cameras. In: Kolb, A., Koch, R. (eds) Dynamic 3D Imaging. Dyn3D 2009. Lecture Notes in Computer Science, vol 5742. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03778-8_2
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DOI: https://doi.org/10.1007/978-3-642-03778-8_2
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