This week, we stayed our course by ordering Nvidia Jetson Nano’s, two camera evaluation boards, card shoes, and card decks. Once they arrive (hopefully this weekend), I will bring up my Jetson Nano and start taking photos.
We purchased two camera modules that have a different sensor resolution and framerate. This will allow us to experiment with different resolutions without needing to wait another week for shipping. The cameras go up to 180fps, and we estimate we need a high FPS to avoid motion blur during quick card movements.
The primary camera I am interested in has the following specs:
- Up to 1280×800@120fps
- 30mm minimum object distance
- 75deg horizontal field of view.
With the camera 3cm away from the playing card, this images a 46mm (1.81in) area with 0.058mm horizontal resolution at 180fps. This is the closest distance to stay in focus. This resolution should be more than sufficient for card classification when the rank and suit are on the imaging plane.
This brings me to another challenge for the project: image selection before classification. When the card trips the sensor, the camera will spam photos to the Jetson Nano. Since we will likely use a camera that has a small imaging plane (ex. 1.81in tall), we will need to choose a valid image to classify. I hope to choose this with _priors_. From the sensor, we will know how long it took to move the card over the camera. Using prior knowledge of Bicycle Standard cards, we can estimate approximately which images contain the rank and suit by assuming constant velocity. While I hope this solution will work, I will have to examine it once we have prototyped the imaging system.
I adjusted our schedule to account for ordering parts on Thursday. I began exploring lens distortion correct methods, but I’ll need the camera in-hand to actually implement that. I am otherwise on schedule.