Agenda
- Data / Visualization framework in Python
- API framework/usage guidelines
- input format
- output format
- Gui to inspect the data.
- Original Data view
- subsection view (using the rotated and subselected image parts).
- Slider to adjust the time.
- Play function.
- Replay speed adjustment.
- Basic statistics of the shown data (e.g. histogramms of the two images, min, max, mean, boxplots, number of blobs [1], …).
- Symmetry measurements
- Develop measures and visualization tools to detect asymmetries between the two images.
- Find examples of such asymmetries.
- Analyze them.
- Occlusion removal
- Classical CV approach
- Learning-based approach(De-Occlusion)
- Abnormality detection
- Thesis writing
Topic 1: Data / Visualization framework in Python
Deliverables due to September
use pandas dataframe library
Topic 2: Symmetry measurements
Deliverables due to October:
- Develop automatic detection methods and selection tools for your guidance
- e.g., highlight these events in your time-line in the gui with red bars, or create a list of events that can be selected
Topic 3: Occlusion removal
Concerned about its appicability to this project. we cannot assume it will work with non-face data
If we don’t know the dynamics of the liquid we cannot reconstruct maintaining the true underlying information.
due to November
https://arxiv.org/pdf/1612.08534.pdf
https://github.com/zhaofang0627/face-deocc-lstm
Next Steps
- Abnormality detection
- due December
- Thesis writing
- due January