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Binocular Stereo Vision FPGA System

This project implements a binocular stereo vision system on an FPGA platform. It uses a binocular module to capture images from different positions, caculates the positional deviation between the corresponding points in these two images, and outputs the diparity diagram and the depth information on a HDMI monitor.

This project is originally designed for a student contest in the 2019 SEU-Xilinx International Summer School.

Sincere appreciation to Xilinx for sponsoring this project.

Quick Instructions

Here are instructions about how to setup this stereo vision system on your FPGA board.

Prerequisites

  • Xilinx Vivado (including SDK & HLS) 2018.2
  • PYNQ-Z2 Development Board
  • A binocular vision module with two OV5640 cameras
  • A HDMI monitor

This project is developed and tested with Xilinx Vivado Suite 2018.2, but it should work with newer versions.

The PYNQ operating system is not used in this project, so you can port this project to other ZYNQ platforms at will.

This PYNQ-Z2 board has only two PMOD interfaces, so we connect the FPGA with the binocular module by the Raspberry PI GPIOs.

Generate HLS IPs

The stereo vision component is written in Vivado HLS, so please follow these steps to generate and export the IP core.

All the relevant HLS C++ files can be found in \$REPO_PATH/hls/src.

A Tcl script named make.tcl is included in \$REPO_PATH/hls. You can use vivado_hls to execute it in the Vivado HLS Prompt.

vivado_hls $REPO_PATH/hls/make.tcl

This project will create a HLS project in \$REPO_PATH/work/sv_hls, and you need to extract the exported IP to the IP repository folder (\$REPO_PATH/ip_repo). The following Vivado building scripts will search for third-part and user-defined IP cores in this folder.

Build Vivado Project

You can "source" scripts in your Vivado Tcl Console to build the Vivado project. These scripts will import RTL files, third-part IPs, SDK C++ files and other necessary files.

set argv [list project=sv_fpga sdk=yes version_override=yes]
set argc [llength $argv]
source "$REPO_PATH/hw/make.tcl" -notrace

Due to the maximum path length limitation on Windows (<260), do NOT specify a very long project name. The default building path is \$REPO_PATH/work/\$PROJ_NAME.

Citation

if this paper is useful for you, please quote as below.

Gang Wu, Jinglei Yang, Hao Yang: Real-time low-power binocular stereo vision based on FPGA. J. Real Time Image Process. 19(1): 29-39 (2022)

References

1.Adams, J.K., Thomas, D.E.: The design of mixed hardware/software systems. In: Proceedings of the 33rd annual Design Automation Conference (DAC’96). Association for Computing Machinery, New York, NY, USA, pp515–520. (1996) https://doi.org/10.1145/240518.240616

2.Ambrosch, K., Humenberger, M., Kubinger, W., Steininger, A.:SAD-Based stereo matching using FPGAs. In: Kisačanin, B.,Bhattacharyya, S.S., Chai, S. (eds.) Embedded Computer Vision.Advances in Pattern Recognition. Springer, London, pp.121-138. https://doi.org/10.1007/978-1-84800-304-0_6

3.Finnerty, A., Ratigner, H.: Reduce Power andCost by Converting from Floating Point to FixedPoint, WP491 (v1.0). Xilinx (2017). https://www.xilinx.com/support/docum entation/white_papers/wp491-floating-to-fixed-point.pdf

4.Angoletta, M.E.: Digital signal processor fundamentals and system design. In : CAS-CERN Accelerator School: Digital Signal Processing,pp.167–229 (2008)

5.Bouguet, J.Y.: Fifth calibration example - calibrating a stereo system, stereo image rectification and 3d stereo triangulation.http://www.vision.caltech.edu/bougu etj/calib_doc/htmls/example5.html

6.Bouguet, J.Y.: Camera calibration toolbox for matlab (2015).http://www.vision.caltech.edu/bouguetj/calib_doc/

7.Crockett, L.H., Elliot, R.A., Enderwitz, M.A., Stewart, R.W.: TheZynq Book: Embedded Processing with the Arm Cortex-A9 on the Xilinx Zynq-7000 All Programmable Soc. Strathclyde Academic Media, Glasgow (2014)

8.DeMicheli, G., Sami, M.: Hardware/software Co-design,. Springer Science & Business Media, Berlin 310 (2013)

9.Einspruch, N.: Application Specific Integrated Circuit (ASIC)Technology, vol. 23. Academic Press, Cambridge (2012) 10.Fetić, A., Jurić, D., Osmanković, D.: The procedure of a camera calibration using Camera Calibration Toolbox for MATLAB, In:Proceedings of the 35th International Convention MIPRO, pp.1752-1757(2012)

11.Geiger, A., Roser, M., Urtasun, R.: Efficient Large-Scale Stereo Matching. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) Computer Vision – ACCV 2010. Lecture Notes in Computer Science,vol.6492. Springer, Berlin, Heidelberg.(2011). https://doi.org/10.1007/978-3-642-19315-6_3

12.Guo, Y., Yao, Y., Di, X.: Research on Structural Parameter Optimization of Binocular Vision Measuring System for Parallel Mechanism. In: 2006 International Conference on Mechatronics and Automation, pp. 1131-1135 (2006) https://doi.org/10.1109/ICMA.2006.257784

13.Jin, S., Cho, J., Dai Pham, X., Lee, K.M., Park, S.K., Kim, M.,Jeon, J.W.: Fpga design and implementation of a real-time stereo vision system. IEEE Trans. Circuits Syst. Video Technol. 20(1),15–26(2009)

14.Li, J., Wu, J., You, Y., Jeon, G.: Parallel binocular stereo-visionbased gpu accelerated pedestrian detection and distance computation.J. Real-Time Image Process. 17(3), 447–457(2020)

15.Lin, C.Y., Chiu, Y.P., Lin, C.Y., Tsai, C.R.: Development of a binocular vision-based catcher robot system using dsp platform. J. Chin. Inst. Eng. 37(2), 210–223 (2014)

16.Madisetti, V., Madisetti, V.: VLSI Digital Signal Processors. Butterworth-Heinemann, Oxford (1995)

17.Mahammed, M.A., Melhum, A.I., Kochery, F.A.: Object distance measurement by stereo vision. Int. J. Sci. Appl. Inform. Technol.(IJSAIT) 2(2), 05–08 (2013) 18.Nan, Y.: Binocular vision system based on pynq (2017). http://www.digilent.com.cn/project/details/140.html

19.Pan, Y., Zhu, M., Luo, J., Qiu, Y.: A Hardware/Software Codesign Approach for Real-Time Binocular Stereo Vision Based on ZYNQ (Short Paper). In: Gao, H., Wang, X., Yin, Y., Iqbal, M. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 268. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-12981-1_50

20.Pérez-Patricio, M., Aguilar-González, A.: Fpga implementation of an efficient similarity-based adaptive window algorithm for realtime stereo matching. J. Real-Time Image Process. 16(2), 271–287 (2019) 21.Perri, S., Frustaci, F., Spagnolo, F., Corsonello, P.: Design of Real-Time FPGA-based Embedded System for Stereo Vision. In: 2018 IEEE International Symposium on Circuits and Systems (ISCAS),pp. 1–5 (2018).https://doi.org/10.1109/ISCAS.2018.8351886

22.Rahnama, O., Cavallari, T., Golodetz, S., Tonioni, A., Joy, T., Di Stefano, L., Walker, S., Torr, P.H.: Real-time highly accurate dense depth on a power budget using an fpga-cpu hybrid soc.IEEE Trans. Circ. Syst. II 66(5),773–777(2019)

23.Rodriguez-Andina, J.J., Moure, M.J., Valdes, M.D.: Features, design tools, and application domains of fpgas. IEEE Trans. Ind.Electron.54(4),1810–1823(2007)

24.Salmen, J., Schlipsing, M., Edelbrunner, J., Hegemann, S., Lüke, S.: Real-time stereo vision: making more out of dynamic programming. In: International Conference on Computer Analysis of Images and Patterns,pp. 1096–1103.Springer(2009)

25.Scharstein, D., Szeliski, R.:A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int.J.Comput.Vis.47(1),7–42(2002)

26.Schauwecker, K.: Real-Time Stereo Visionon FPGAs with SceneScan (2018).CoRRabs/1809.07977

27.Tang, Y., Pang, C., Zhou, Z., Chen, Y.: Binocularomni-directional vision sensor and epipolar rectification in its omni-directional images.J. Zhejiang Univ. Technol. 1,20 (2011)

28.Werner, M., Stabernack, B., Riechert, C.: Hardware implementation of a full hd real-time disparity estimation algorithm. IEEE Trans. Consumer Electron. 60(1),66–73 (2014)

29.Yan, Y., Zhu, Q., Lin, Z., Chen, Q.: Camera Calibration in Binocular Stereo Vision of Moving Robot. In: 2006 6th World Congress on Intelligent Control and Automation,pp. 9257–9261. https://doi.org/10.1109/WCICA.2006.1713792

30.Zhang, K., Lu, J., Lafruit, G., Lauwereins, R., Gool, L.V.: Realtime accurate stereo with bitwise fast voting on CUDA. In: 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCVWorkshops,pp.794-800(2009). https://doi.org/10.1109/ICCVW.2009.5457623

31.Zhang, Z.: A flexible new technique for camera calibration. IEEETrans. Pattern Anal.Mach.Intell.22(11),1330–1334(2000)

Contributors

This is an open-source project, so if you want to contribute, just open issues and create pull-requests.

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Real-time binocular stereo vision FPGA system with OV5640 cameras

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