Abstract
This paper introduces a fusion algorithm to integrate low-resolution depth maps and stereo matching algorithms. Our fusion algorithm is a divide-and-conquer approach that produces a number of disparity maps over many small sections, named stripes, of the stereo images. The algorithm then uses statistical methods to evaluate each of these sections in order to produce an accurate high-resolution disparity map for a given scene.
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References
Badino, H., Huber, D., Kanade, T.: Integrating LIDAR into Stereo for Fast and Improved Disparity Computation. In: 3DIMPVT (2011)
Bouguet, J.Y.: Camera Calibration Toolbox for Matlab
Guerra-Filho, G.: An Optimal Time-Space Algorithm for Dense Stereo Matching. The Journal of Real-Time Image Processing (2010)
Gurram, P., Rhody, H., Kerekes, J., Lach, S., Saber, E.: 3d Scene Reconstruction Through a Fusion of Passive Video and LIDAR Imagery. In: 36th Applied Imagery Pattern Recognition Workshop (2007)
Hahne, U., Alexa, M.: Combining Time-of-Flight Depth and Stereo Images Without Accurate Extrinsic Calibration. International Journal of Intelligent Systems Technologies and Applications (2008)
Kim, Y.M., Theobalt, C., Diebel, J., Kosecka, J., Miscusik, B., Thrun, S.: Multi-View Image and TOF Sensor Fusion for Dense 3D Reconstruction. In: 3DIM (2009)
Kuhnert, K., Stommel, M.: Fusion of Stereo-Camera and PMD-Camera Data for Real-Time suited precise 3d environment reconstruction. In: IROS (2006)
Scharstein, D., Szeliski, R.: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. International Journal of Computer Vision 4 (April-June 2002)
Mutto, C., Zanuttigh, P., Cortelazzo, G.: A probabilistic approach to tof and stereo data fusion. In: 3DPVT10 (2010)
Nickels, K., Castano, A., Cianci, C.M.: Fusion of lidar and stereo range for mobile robots. In: International Conference on Advanced Robotics (2003)
Zhu, J., Wang, L., Yang, R., Davis, J.: Fusion of timeof-fight depth and stereo for high accuracy depth maps. In: CVPR (2008)
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© 2012 Springer-Verlag Berlin Heidelberg
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Fortenbury, B.R., Guerra-Filho, G. (2012). Fusing Low-Resolution Depth Maps into High-Resolution Stereo Matching. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33179-4_16
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DOI: https://doi.org/10.1007/978-3-642-33179-4_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33178-7
Online ISBN: 978-3-642-33179-4
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