- What did you personally accomplish this week on the project? Give files or photos that demonstrate your progress. Prove to the reader that you put sufficient effort into the project over the course of the week (12+ hours).
I finished implementing Local PCA. The program takes in an arbitrary number of images, classes, and allows variable settings for eigenvectors chosen. It shows the reconstructions of all input images and also shows the k-means clustering results in a 3D plot. The clustering was not very good. After speaking with the professor, we decided we needed either more data, more eigenvectors, or to likely use LDA. We also started working on using dlib library to understand where the eyes in an image are so we can transform the image to get a frontal view.
- Is your progress on schedule or behind? If you are behind, what actions will be taken to catch up to the project schedule?
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- On schedule.
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- What deliverables do you hope to complete in the next week?
- Improve our PCA performance. Implement or use library K-mean to cluster points and take a step closer to performing the actual recognition.