PRiMEStereoMatch

Theoretical Background
A heterogeneous and fully parallel stereo matching algorithm for depth estimation. Stereo Matching is based on the disparity estimation algorithm, an algorithm designed to calculate 3D depth information about a scene from a pair of 2D images captured by a stereoscopic camera. The algorithm contains the following stages:
- Cost Volume Construction - weighted absolute difference of colours and gradients function.
- Cost Volume Filtering - Adaptive Support Weight (ADSW) Guided Image Filter (GIF) function.
- Disparity Selection - Winner-Takes-All (WTA) minimum cost selection.
- Post Processing - left-right occlusion check, invalid pixel replacement and weight-median filtering.

Implementation Details
- All stages of the algorithm have been developed in both C++ and OpenCL.
- C++ parallelism is introduced via the POSIX threads (pthreads) library. Disparity level parallelism is supported, enabling up to 64 concurrent threads.
- OpenCL parallelism is inherent through the concurrent execution of kernels on an OpenCL-compatible device. The optimum level of parallelism will be bounded by the platform & devices.
- Support for live video disparity estimation using the OpenCV VideoCapture interface as well as static image computation.
- Embedded support for experimentation with the OpenCV standard Semi-Global Block Matching (SGBM) algorithm.
Installation
Prerequisites
- Hardware:
- Development Platform - optionally but ideally including OpenCL compatible devices
- Software:
Compilation
- Download project folder to your platform.
- Enter the base directory using
cd DE_APP.
- Natively compile the project using
make -jN.
- Set N to the number of simultaneous threads supported on your compilation platform, e.g. 8.
Deployment
- Run the application using
./bin/Release/DE_APP <program arguments>
- The following program arguments must be specified:
- Matching Algorithm type:
- STEREO_GIF - Guided Image Filter
- STEREO_SGBM - Semi Global Block Matching
- Media type:
- When specifying the VIDEO media type, the following optional arguments can be included:
- RECALIBRATE - recalculate the intrinsic and extrinsic parameters of the stereo camera. Previously captured chessboard images must be supplied if the RECAPTURE flag is not also set.
- RECAPTURE - record chessboard image pairs in preparation for calibration. A chessboard image must be presented in front of the stereo camera and in full view of both cameras. Press the R key to capture a frame. The last frame captured is shown beneath the video stream.
- For example, to run with the guided image filter algorithm using a stereo camera, specify:
./bin/Release/DE_APP STEREO_GIF VIDEO
- To run with calibration and capture beforehand, specify:
./bin/Release/DE_APP STEREO_GIF VIDEO RECALIBRATE RECAPTURE
-
Image disparity estimation is achieved using for example:
./bin/Release/DE_APP STEREO_GIF IMAGE left_img.png right_img.png
-
The first time the application is deployed using a stereo camera, the RECALIBRATE and RECAPTURE flags must be set in order to capture chessboard image to calculate the intrinsic and extrinsic parameters.
- This process only needs to be repeated if the relative orientations of the left and right cameras are changed or a different resolution is specified.
- Once the intrinsic and extrinsic parameters have been calucalted and saved to .yml files, the application can be re-run with the same camera without needing to recalibrate as teh parameters will be loaded from these files. The files can be found in the data directory.
Interactivity
- Press h to display a help menu on the command line. This shows input and control options for the program which change the way the algorithm behaves for the next frame.
- Control Options:
- Numbers 1 - 8: change the number of threads created by the process
- m: switch the computational mode between OpenCl and pthreads
- t: switch the data type use for processing between 32-bit and 8-bit
- Control options are only available for the STEREO_GIF matching algorithm.
Additional Resources
Directory Structure
DE_APP - Project top level directory
folders:
assets - OpenCL kernel files
bin - binary executable files
common - OpenCL common utility/helper functions (C) ARM Ltd
data - program data including input images, stereo camera parameters, calibration images, etc
include - Project header files (h/hpp)
src - Project source files (c/cpp)
files:
cbp2make.linux-x86_64 - codeblocks project to makefile tool (for x86_64 PC - see (https://sourceforge.net/projects/cbp2make/) for sourceforge project)
cbp2make_usage.txt - cbp2make tool manual
DE_APP.cbp - Code::Blocks project file
DE_APP.depend - Code::Blocks settings file
DE_APP.layout - Code::Blocks settings file
main.cpp - main C++ file
Makefile - project Makefile
References
Code
CrossScaleStereo - The basis for some C++ DE functions (GNU Public License)
Literature
[Hosni2011CVPR]: C. Rhemann, A. Hosni, M. Bleyer, C. Rother, and M. Gelautz. Fast cost-volume filtering for visual correspondence and beyond. In CVPR, 2011
[Hosni2011ICME]: A. Hosni, M. Bleyer, C. Rhemann, M. Gelautz and C. Rother, Real-time local stereo matching using guided image filtering, in Multimedia and Expo (ICME), 2011 IEEE International Conference on, Barcelona, 2011.
[Ttofis2014]: C. Ttofis and T. Theocharides, High-quality real-time hardware stereo matching based on guided image filtering, in Design, Automation and Test in Europe Conference and Exhibition (DATE), Dresden, 2014.
[He2012]: K. He, J. Sun and X. Tang, Guided Image Filtering, Pattern Analysis and Machine Intelligence, IEEE Transactions on, pp. 1397-1409, 02 October 2012.
License
This software is released under the BSD 3 Clause License. See LICENSE.txt for details.