Next important dates:
- March 18th-29th: Organization Application deadline.
- April 8th: Announcement of GSoC Mentoring Orgs. (whether we're in or out)
- April 9th-21st: POTENTIAL INTERNS: Discuss project ideas with us gsoc2013@itseez.com
- April 22-May 3rd: Application period
- May 8th: Slot allocations published
- May 22nd 12-1PST Dedup meeting
- May 27th Final project decisions are made
- June 17th: Let's start coding !!!
Project Idea summary
April 9th-21st: Discuss projects below or other ideas with us gsoc2013@itseez.com
Students may propose their own projects
- Mobile vision app development
Clear "hello world" type of example to make it easier for the rest to start developing mobile vision applications. ios o android examples
-Computational Photography
SUpport mobile cameras on tablets and phones
- noise estimation and reduction,
- tilt-shift images and movies,
- multi-focal point images,
- high dynamic range images by composition with different shutter times
Vision Applications:
working functionality.
- Automatically generating comics
- Image Collage -- use python to make it easy to put together a collage of images from a trip etc
- Annotate the images
- Do effects like comic life http://plasq.com/products/comiclife/win
- Hand tracking with the kinect - C++
- Movie editor with effects. Simple, intuitive to use ???????
- Point cloud view using depth in OpenCV arrays
OpenCL Optmization
Mech Turk Interface
- Easily label images for train test in OpenCV ???
1D and 2D Barcode readers
- We have a basic datamatrix reader. Expand to other kinds of barcodes (1D, other 2D).
Natural barcodes
OpenCV can read calibration patterns. Calibrate a camera, rectify it's output. Put a picture next to a calibration pattern in a scene. Find 2D interest points with features2D. Measure them in the image using the calibration pattern. Use the pattern of interest points and their measures to turn the picture into a calibration pattern/barcode so that the computer recognizes the picture and knows where it is in relation to the iamge.
- Stretch goal, embeded and retrieve watermarks in the image.
Python examples
Tutorials
Continue with OpenCV Tutorials
Inverted index
create an inverted index of functionality to functions ---- FACIL
more Qt integration ----PREGUNTAS
- multiwindow ????
- visual output for certain algorithm during the execution (for the different steps)
- visualizer for SfM (basic OpenGL and Qt integration), e.g. : http://www.youtube.com/watch?v=jZlhnguoBag
SfM integration:
- Ceres integration (we need some BA stuff). It depends on Eigen but they just changed their license and that could be a micro-module
Matlab integration: --- PREGUNTAR
- we could have somebody writing samples/testing the latest wrapper. Needs: OpenCV knowledge a bit, Python knowledge. Write a script
that takes output from parser (list of classes/methods/functions) and generates C code that is Matlab wrappers (mex knowledge). Find solution to deal with row-major/col major
multi-camera calibration:
- that should be its own micro-module
RGBD functions: ---PREGUNTAR
- We already have normal, plane finder, ICP, we could have more maybe: octrees, plane-plane ICP, depth cleaner ...
Full LINE-MOD implementation: ----- NO
- That would focus on the ACCV paper for pre/post processing
Course-ware: --- PREGUNTAR
- We want to start offering vision courses using OpenCV.
- If you are expert in a topic (say it's your area of graduate research, or you've just finished a project or course in a particular topic and can explain it well)
- Write up the topic, the math and then develop a step by step example of it using OpenCV.
Generic numerical optimization module:
- We want to have the package of general purpose optimization methods that can be easily used in computer vision algorithms (ex. downhill simplex method, annealing particle filter).
- This will require a mathematically inclined student and/or one who has taken course work in the area obviously
PYTHON
Expose OpenCV GPU functionality into Python API
- Current Python OpenCV wrappers use
cv::Mat<=> Numpy array mapping for passing data between C++ and Python worlds. Aim of this project is to adopt PyCuda GPUArray as a counterpart ofGpuMat. - This would allow to extend cv2 wrapper generator to expose CUDA-powered OpenCV functions.
- Project requires good knowledge of C++ and Python and willingness to dive into the internals of OpenCV, Python and PyCuda.
- Expect all sorts of gotchas, subtle issues and design discussion with mentors.
- The resulting design decisions can be used to wrap the OpenCV's OpenCL functionality with PyOpenCL
GSOC OPENCV APPLICATION - ORG
MENTORES
No hay comentarios:
Publicar un comentario