Jason Huang
Accomplishments:
- Found additional sources for creating Face Curvature Maps and implementing Similarity Matching Schema
- Completed implementation of evaluating facial curvature maps
- Started on implementing Similarity Matching Schema, based on paper An Introduction to Biometric Recognition by Anil K. Jain, Arun Ross
- Created slides for Design Review presentation
Upcoming Work
Next week, I would like to finish implementing the similarity matching schema based on the algorithm provided by the paper. With our cameras arriving soon, I would also like to get started working on 3D facial pre-processing, so I can use the data points to create a facial curvature map and test different functions that I have written so far.
Schedule
I am currently on schedule. As stated from last week, there are four parts to the algorithm and I plan on tackling each section on a weekly basis. Instead of implementing Viola-Jones, I plan on using 3D data from the RGB camera instead, which eases the workload a bit.
Joe Zhao
This week I talked to Professor Kelly about the preliminary inductive power circuit. He advised to tune the circuit in series instead of parallel, in order to deliver greater current through the inductor. I spent the next few days tuning that circuit, but then we decided to move the raspberry pi to the front, increasing the amount of power needed. During the period where we were debating this issue, I designed the front power circuitry, as well as the backup battery circuit for the back. Parts will need to be spec’d again.
Last week my hope was to begin implementing the power system with parts ordered, but since there was a change in the location of our primary computation, I will need to redo the math in order to get the proper power delivery. In lieu of this, I decided to design the front power system, thereby still completing a weeks worth of work, just moving things around as we came to a decision. Now that we have decided on the location of the RPI, I hope to deliver a working power delivery system that can send 4W. This will be sufficient to power the rpi during idle and the camera. Then, during active power consumption, capacitors in parallel will be able to supply peak power during the 5secs of computation.
Emily Wong
This week I spent a good amount of time trying to figure out how to get our depth camera to talk with our microcontrollers so that we would be able to use Intel’s SDK to get RGB and depth pictures. There was a lot of conflicting information on whether the camera’s USB 3.0 was backwards compatible with USB 2.0, but I wasn’t able to test since the cable didn’t come with the camera.. 🙁 Other than that, I’ve started wiring things together (LED’s and buttons to microcontroller) to get the base of the front started.
Next week will be primarily spent on getting camera data so that Jason can finally base his algorithm on concrete data (which is what this week was for but there were a lot of problems [see above]). Once I get the cable, I’ll be able to test out getting data from the camera through the microcontroller, and since I’ve already been working on the base for the front, it shouldn’t be that bad to get back on track, since according to schedule I should be working on having the bluetooth modules send data (permit/deny) back and forth.
Team
We worked on the design review slides this week, and had some discussions mostly based around the camera problems we were having. We found that the Raspberry Pi 4 has USB 3.0 ports, so we changed our design so that our computation for facial recognition was in the front rather than the back, meaning that the bluetooth should only be used for sending state/decisions for locking/unlocking. Other than that, everything seems to be mostly on track, and everyone has a good understanding of what everyone else is doing, so help is abundant 🙂