Heidi’s Status Report for 2/27

This week I practiced for the proposal presentation on Wednesday. Based on the feedback we received about upgrading from the Jetson Nano to the Jetson Xavier NX, I went back and did some more research between the two microprocessor options. The Xavier NX has a plug-in WLAN and Bluetooth module with antennas which would save us the cost of buying an Intel Wifi Card to add onto the Nano. From the introduction video, one of the demo’s they showed included Gaze estimation which used NVIDIA facial landmarks which uses the CMU Multi-PIE Face Database. This gave a bit more clarification for me on the region keypoint pixel error that was mentioned during our proposal presentation for facial landmarking metrics. From our feedback on our status reports, I moved away from research papers to project examples. I looked into an example with OpenCV, Dlib and Python to begin experimenting with facial detection and landmarking. I have downloaded the necessary packages, including Dlib and its requirements to my laptop to begin working. There were various updates I needed to add to my laptop for Dlib to properly install. I also looked into data sets for head poses, as an option instead of our data collection. The DriveAHead data set and UAH-DriveSet seem like they will be the best for our needs, particularly the UAH-DriveSet.

Progress is on schedule. The proposal presentation went well and we have discussed as a group how to address the suggestions we received and will bring this up in our meeting on Monday with Abha. Our plans to order immediately after the presentation were pushed back because we received the suggestion to upgrade to Xavier NX but after discussing with Abha we should be able to submit the order on Monday.

This next week, we will order the Xavier NX and other hardware components. I will work with my teammates to prepare our design presentation and ensure that we have updated our requirement metrics. I hope to also have a simple facial detection python script working with Dlib and OpenCV.

Sources:

NVIDIA Jetson Xavier NX Developer Kit

https://www.jetsonhacks.com/2020/05/16/nvidia-jetson-xavier-nx-developer-kit/

https://developer.nvidia.com/embedded/learn/get-started-jetson-xavier-nx-devkit#intro

Facial Landmarks Estimation

https://ngc.nvidia.com/catalog/models/nvidia:tlt_fpenet

Facial landmarks with Dlib, OpenCV, and Python

https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/

https://towardsdatascience.com/facial-mapping-landmarks-with-dlib-python-160abcf7d672

Dlib Setup

https://stackoverflow.com/questions/54719496/installing-dlib-in-python-on-mac

Data set