European Journal of Business Science and Technology 2016, 2(2):160-168 | DOI: 10.11118/ejobsat.v2i2.66
The Stereoscopic Analysis and Depth Map Creation
- 1 Mendel University in Brno, Czech Republic
This contribution is focused on the use of the stereoscopic image for the purpose of depth map creation. Further, methods for calibration of the camera(s) are discussed. A stereoscopic head was constructed for the purpose of creating a stereoscopic image. Two Basler acA1600-20uc industrial cameras with Computar M2514-MP2 lenses were used for constructing this head. Furthermore, the algorithm for obtaining the depth map is described. The programming language C# and EmguCV library were used for the implementation of the algorithm. The algorithm consists of 4 parts. The calibration of the camera(s) and image acquisition is solved as first. Calibration of the camera(s) is solved by detection of intersections on the chessboard. Further, methods for the purpose of obtaining the depth map are described. Finally the implemented algorithm is tested.
Keywords: stereoscopic image, depth map, EmguCV, Basler
JEL classification: L86
Published: December 30, 2016 Show citation
References
- Bennett, S. and Lasenby, J. 2014. ChESS - Quick and Robust Detection of Chess-Board Features. Computer Vision and Image Understanding, 118, 197-210.
Go to original source...
- Cao, X. and Foroosh, H. 2006. Camera Calibration Using Symmetric Objects. IEEE Transactions on Image Processing, 15 (11), 3614-3619.
Go to original source...
- Chen, G., Guo, Y., Wang, H., Ye, D. and Gu, Y. 2012a. Stereo Vision Sensor Calibration Based on Random Spatial Points Given by CMM. Optik - International Journal for Light and Electron Optics, 123 (8), 731-734.
Go to original source...
- Chen, J., Benzeroual, K. and Allison, R. S. 2012b. Calibration for High-Definition Camera Rigs with Marker Chessboard. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 29-36.
Go to original source...
- Chu, J., GuoLu, A. and Wang, L. 2013. Chessboard Corner Detection under Image Physical Coordinate. Optics & Laser Technology, 48, 599-605.
Go to original source...
- de la Escalera, A. and Armingol, J. M. 2010. Automatic Chessboard Detection for Intrinsic and Extrinsic Camera Parameter Calibration. Sensors, 10 (3), 2027-2044.
Go to original source...
- Devy, M., Garric, V. and Orteu, J. J. 1997. Camera Calibration from Multiple Views of a 2D Object, Using a Global Nonlinear Minimization Method. In: Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems, pp. 1583-1589.
Go to original source...
- Dröppelmann, S., Hueting, M., Latour, S. and van der Veen, M. 2010. Stereo Vision using the OpenCV Library. [online]. Available at: https://pdfs.semanticscholar.org/8149/5e6c1e6c3460b14f4be8e7876f1d6659f5c1.pdf. [Accessed 2016, December 20].
- Emgu CV. 2012. Stereo Imaging. [online]. Available at: http://www.emgu.com/wiki/index.php/Stereo_ Imaging. [Accessed 2016, December 8].
- Fathi, H. and Brilakis, I. 2016. Multistep Explicit Stereo Camera Calibration Approach to Improve Euclidean Accuracy of Large-Scale 3D Reconstruction. Journal of Computing in Civil Engineering, 30 (1).
Go to original source...
- George, M. A. and George, A. M. 2014. Stereovision for 3D Information. In: Babu, B. V. et al. (eds.). Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), pp. 1595-1602.
Go to original source...
- Gu, W., Yin, J., Yang, X. F. and Liu, P. 2014. Disparity Map Acquisition Based on Matlab Calibration Toolbox and OpenCV Stereo Matching Algorithm. Advanced Materials Research, 926-930, 3030-3033.
Go to original source...
- Kamencay, P., Brezňan, M., Jarina, R., Lukáč, P. and Zachariáąová, M. 2012. Improved Depth Map Estimation from Stereo Images based on Hybrid Method. Radioengineering, 21 (1), 70-78.
- Kolomazník, J., Ondrouąek, V. and Vytečka, M. 2013. Stereoscopic Analysis of the Technological Scene. In: 19th International Conference on Soft Computing MENDEL 2013. Brno: Vysoké učení technické v Brně, pp. 353-356. ISBN 978-80-214-4755-4.
- Laureano, G. T., de Paiva, M. S. V., da Silva Soares, A. and Coelho, C. J. 2015. A Topological Approach for Detection of Chessboard Patterns for Camera Calibration. Emerging Trends in Image Processing, Computer Vision and Pattern Recognition, chapter 34, pp. 517-531.
Go to original source...
- Lindner, M., Schiller, I., Kolb, A. and Koch, R. 2010. Time-of-Flight Sensor Calibration for Accurate Range Sensing. Computer Vision and Image Understanding, 114 (12), 1318-1328.
Go to original source...
- National Instruments. 2016. 3D Imaging with NI LabVIEW. [online]. Available at: http://www.ni.com/white-paper/14103/en/. [Accessed 2016, April 10].
- Placht, S., Fürsattel, P., Mengue, E. A., Hofmann, H., Schaller, C., Balda, M. and Angelopoulou, E. 2014. ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration. In: Fleet, D. et al. (eds.). ECCV 2014, Part IV, pp. 766-779.
Go to original source...
- Prokos, A., Kalisperakis, I., Petsa, E. and Karras, G. 2012. Automatic Calibration of Stereo-Cameras Using Ordinary Chess-Board Patterns. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B5, 45-49.
Go to original source...
- Rambhia, J. 2013. Disparity Map. [online]. Available at: http://www.jayrambhia.com/blog/disparity-mpas. [Accessed 2016, October 31].
- Revuelta Sanz, P., Ruiz Mezcua, B., Sánchez Pena, J. M. and Thiran, J.-P. 2011. Stereo Vision Matching over Single-Channel Color-Based Segmentation. In: Proceedings of the International Conference on Signal Processing and Multimedia Applications (SIGMAP), pp. 126-130.
Go to original source...
- Sun, J., Liu, Q., Liu, Z. and Zhang, G. 2011. A Calibration Method for Stereo Vision Sensor with Large FOV based on 1D Targets. Optics and Lasers in Engineering, 49 (11), 1245-1250.
Go to original source...
- Wang, F., Jia, K. and Feng, J. 2017. The Real-Time Depth Map Obtainment Based on Stereo Matching. In: Pan, J. et al. (eds.). Intelligent Data Analysis and Applications, pp. 138-144.
Go to original source...
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