/CS205-ImageStitching

Real Time Image Stitching

Primary LanguageC++MIT LicenseMIT

Real-Time Image Stitching

CS205 Computing Foundations for Computational Science Final Project

Harvard University, 2018 Spring

Team members: Weihang Zhang, Xuefeng Peng, Jiacheng Shi, Ziqi Guo

This page only provides technical documentations about the project. For a complete view of our project including motivation, design approach, results and analysis, please head over to the project website.

Project Goal

Image stitching or photo stitching is the process of combining multiple photographic images with overlapping fields of view to produce a segmented panorama or high-resolution image (example below).

(source: http://www.arcsoft.com/technology/stitching.html)

In this project, we want to use big compute techniques to parallelize the algorithms of image stitching, so that we can stream videos from adjacent camera into a single panoramic view.

Instructions

Compile Dependencies:

  • GCC 6 or higher
  • OpenCV 3.4.0 or higher
  • pkg-config

Compile:

cd to one of the surf_sequential/, surf_omp/, or surf_openacc/ folders before compiling your code.

Sequential Version

MacOS:
g++-7 -std=c++11 -fpermissive -o test main.cpp fasthessian.cpp integral.cpp ipoint.cpp surf.cpp utils.cpp `pkg-config opencv --cflags --libs`

Adapt g++-7 to the version of g++.

Ubuntu:
g++ -std=c++11 -fpermissive -o test main.cpp fasthessian.cpp integral.cpp ipoint.cpp surf.cpp utils.cpp `pkg-config opencv --cflags --libs`

OpenMP Version

MacOS:
g++-7 -fopenmp -std=c++11 -fpermissive -O3 -o test main.cpp fasthessian.cpp integral.cpp ipoint.cpp surf.cpp utils.cpp `pkg-config opencv --cflags --libs`

Adapt g++-7 to the version of g++.

Ubuntu:
g++ -fopenmp -std=c++11 -fpermissive -O3 -o test main.cpp fasthessian.cpp integral.cpp ipoint.cpp surf.cpp utils.cpp `pkg-config opencv --cflags --libs`

OpenACC Version

The OpenACC version can only be compiled and run on a device with GPU. Before compiling, set the environment with source env.sh.

Machine with GTX GPU:
pgc++ -acc -ta=tesla:cc60 -Minfo -std=c++11 -O3 -o test main.cpp fasthessian.cpp integral.cpp ipoint.cpp surf.cpp utils.cpp `pkg-config opencv --cflags --libs`
Machine with Tesla GPU:
pgc++ -acc -ta=tesla -Minfo -std=c++11 -O3 -o test main.cpp fasthessian.cpp integral.cpp ipoint.cpp surf.cpp utils.cpp `pkg-config opencv --cflags --libs`

Run Test Cases:

To run test cases, first compile with instructions above, but without using any parallelization (for OpenMP, remove -fopenmp; for OpenACC, use g++ instead of pgc++).

Then run:

sh sample_test.sh

When the stitched image pops out, press Esc button.

The test shell script will check the output with the standard output running on our development machine. If it does not print anything after "Took: xxx seconds" line, then you are good to go!

For more examples, go to the Example section and follow the command to compare with the correct outputs.

Run:

./test -m <mode> [...]

Argument Options (< > after flag indicates argument is required)

  • -m | --mode < >:

    • 0: run SURF on a single image
    • 1: run static image match between a pair of images
    • 2: run image stitching with webcam stream
    • 3: run image stitching with local video files

  • -b | --blend_mode: (no additional argument)

    • if set, run blending algorithm with stitching; otherwise, run regular stitching algorithm

  • -r | --resolution (for mode 2 and 3 only):

    • user-specified resolution

  • -s | --single_mem_cpy: (OpenACC only)

    • if set, one single mem copy; otherwise, do memory copy from host to device every response layer

  • -t | --threaded: (OpenACC only)

    • if set, using the multi-threading version for task-level parallelization

  • -S/L/R | --src/src1/src2

    • path of image/video to be processed. For mode 0, -S|--src will be used for single image feature extraction; for mode 1 and mode 3, -LR|--src1 --src2 will be used for image/video stitching from local files
    • if flags are not set, will use sample image/video given by this repository

Examples

Mode 0: Run SURF on a single image

  • Command: ./test -m 0

  • Input image:

  • Output image:

Mode 1: Run static image match between a pair of images

  • Command:
Input image 1 Input image 2
  • Output image:

Mode 2: Run image stitching with webcam stream

720P, single memory copy:
720P, single memory copy, with blending:

References