Abstract
Stereo Vision has been a focus of research for decades. In the meantime, many real-time stereo vision systems are available on low-power platforms. Several products using stereo vision exist on the market. So far, all of them are based on image sizes up to 1 MP. They either use a local correlation-like stereo engine or perform some variant of Semi-Global Matching (SGM).
However, many modern cameras deliver 2 MP images (full High Definition) at framerates beyond 20 Hz. In this contribution we propose a stereo vision engine tailored for automotive and mobile applications, that is able to process 2 MP images in real-time. Note that also the disparity range has to be increased when maintaining the same field of view with higher resolution. We implement the SGM algorithm with search space reduction techniques on a reconfigurable hardware platform, yielding a low power consumption of under 1 W. The algorithm runs at 22 Hz processing 2 MP image pairs and computing disparity maps with up to 255 disparities. The conducted evaluations on the KITTI Dataset and on a challenging bad weather dataset show that full depth resolution is obtained for small disparities and robustness of the method is maintained at a fraction of the resources of a regular SGM engine.
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References
Banz, C., et al.: Real-time stereo vision system using SGM disparity estimation: architecture and FPGA-implementation. In: SAMOS Conference (2010)
Banz, C., Blume, H.: Real-time semi-global matching disparity estimation on the GPU using SGM. In: Mobile Vision Workshop ICCV (2011)
Franke, U., Joos, A.: Real-time stereo vision for urban traffic scene understanding. In: Intelligent Vehicles (2000)
Franke, U. et al.: Making bertha see. In: Computer Vision for Autonomous Vehicles Workshop ICCV (2013)
Gehrig, S.K., Eberli, F., Meyer, T.: A real-time low-power stereo vision engine using semi-global matching. In: Fritz, M., Schiele, B., Piater, J.H. (eds.) ICVS 2009. LNCS, vol. 5815, pp. 134–143. Springer, Heidelberg (2009)
Gehrig, S., Rabe, C.: Real-time semi-global matching on the CPU. In: ECVW 2010 CVPR, June 2010
Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? the KITTI vision benchmark suite. In: CVPR, June 2012
Hirschmueller, H.: Accurate and efficient stereo processing by semi-global matching and mutual information. CVPR 2, 807–814 (2005). (San Francisco, CA)
Hirschmueller, H., Gehrig, S.: Stereo matching in the presence of sub-pixel calibration errors. In: CVPR, Miami, FL, June 2009
Hirschmueller, H., Scharstein, D.: Evaluation of stereo matching costs on images with radiometric distortions. IEEE PAMI 31(9), 1582–1599 (2009)
Hirschueller, H., Buder, M., Ernst, I.: Memory-efficient semi-global matching. In: XXII ISPRS Congress (2012)
Konolige, K.: Small vision systems. In: Proceedings of the International Symposium on Robotics Research, Hayama, Japan (1997)
Muehlmann, K., et al.: Calculating dense disparity maps from color stereo images, an efficient implementation. IJCV 47(1–3), 79–88 (2002)
Pfeiffer, D., Gehrig, S., Schneider, N.: Exploiting the power of stereo confidences. In: CVPR, June 2013
Sabihuddin, S., MacLean, W.J.: Maximum-likelihood stereo correspondence using field programmable gate arrays. In: ICVS, Bielefeld, Germany, March 2007
Scharstein, D., Szeliski, R.: Middlebury online stereo evaluation. http://vision.middlebury.edu/stereo. Accessed 12 March 2013
Schumacher, F., Greiner, T.: Matching cost computation algorithm and high speed fpga architecture for high quality real-time semi global matching stereo vision for road scenes. In: ITSC (2014)
Spangenberg, R., Langner, T., Adfeldt, S., Rojas, R.: Large scale semi-global matching on the CPU. In: Intelligent Vehicles (2014)
Tippets, B., et al.: Review of stereo vision algorithms and their suitability for resource-limited systems. Journal of Real-Time Image processing. Springer, Heidelberg, January 2013. http://rd.springer.com/article/10.1007%2Fs11554-012-0313-2
Usami, M., et al.: Stereo vision system for advances vehicle safety system. In: SAE World Congress, Technical paper. 2007–01-0405 (2007)
Woodfill, J.I., et al.: The TYZX deepsea G2 vision system, a taskable, embedded stereo camera. In: Embedded Computer Vision Workshop. pp. 126–132 (2006)
Zabih, R., Woodfill, J.: Non-parametric local transforms for computing visual correspondence. In: Eklundh, J.-O. (ed.) ECCV 1994. LNCS, vol. 801, pp. 151–158. Springer, Heidelberg (1994)
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Gehrig, S.K., Stalder, R., Schneider, N. (2015). A Flexible High-Resolution Real-Time Low-Power Stereo Vision Engine. In: Nalpantidis, L., Krüger, V., Eklundh, JO., Gasteratos, A. (eds) Computer Vision Systems. ICVS 2015. Lecture Notes in Computer Science(), vol 9163. Springer, Cham. https://doi.org/10.1007/978-3-319-20904-3_7
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DOI: https://doi.org/10.1007/978-3-319-20904-3_7
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