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Jae’s Status Report for 3/16/24

This week, I got a good amount of work done. First, I wrapped up the arduino code and was able to control four motors given a string of the format “[motorID1]:[direction1]:[degrees1]&[motorID2]:[direction2]:[degrees2]&…”. I tested the serial communication between python code that simulated Bhav’s end, and was able to simultaneously control four motors given these commands. I am unfortunately missing a few small screws to attach the cameras to the servo brackets, but I did attach the servo brackets to the servos. To finalize building the camera stands, I will be looking for these screws, as well as some form of base to stabilize the motors.

I am mostly back on schedule. With the Arduino code finished, the only part I am behind on is building the camera stand, but that is in progress.

Next week, I hope to have the camera stands finished. I also will try to work on integrating this code with OpenCV’s boundary box output instead of my simulated python code.

(sorry for the blurry code, I can’t seem to find a workaround.)

 

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Thomas’s Status Report for 3/9/24

This week on the project I wrote the design requirement, the implementation plan for the feed selection subsystem, the block diagram for the feed selection subsystem, the risk mitigation plans, the related work, the glossary of acronyms, and the index terms for the design document.

My progress is currently on schedule as there was no scheduled work over the break.

Next week I hope to complete working code for live autonomous switching of camera feeds to display  as a subcomponent for the project subsystem I am working on.

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Bhavya’s Status Report for 03/09/2024

After switching to the F1 track camera idea (post the design presentation) the team had to scramble to establish and work on this new idea.

I started the week off by writing the object tracking algorithm using GOTURN. I also tested several image preprocessing strategies that could possibly reduce the latency of the tracking system. I was able to achieve a preliminary tracking algorithm.

The next major task was the design document submission. I was in charge of the trade studies on computer vision strategies, implementation details of detection and tracking systems, and the outline of the testing and verification in accordance with the use case requirements. We split up the work and conducted peer reviews before finalizing the document.

Over the break, I have been working on the detection algorithm, integrating it with the tracking algorithm, and testing it on the actual slot racing car that we plan to use for the demonstration. I hope to integrate it with the camera to have a one-camera system ready by Wednesday and start arranging the muti-camera system by the end of this week.

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Team Status Report for 3/9/24

As we finalized our design through working on the design doc, the biggest risk of our project is the speed of the car affecting our ability to track it. As of now, we have not done too much on track testing to see if our tracking latency is too slow for a close up camera locations, but our contingency plan is to simply place the cameras further away from the track as needed, to reduce the amount of rotation the camera has to make to track the car.

We made a big switch to change our project to this car tracking one. So in terms of design, we weren’t changing much, just brainstorming for the first time. Through working on the design doc, we were able to come up with challenges we may face, especially in our own parts (hardware, tracking, feed selection). Although we are very late in our idea decision, we are glad we switched as it will be a busy but better experience for all of us.

Our most recently updated schedule is the same as the one submitted on the design document.

Part A was written by Jae Song

On the global scale, our Cameraman product will offer a better approach in live streaming car racing. On the safety side of capturing footage, auto-tracking cameras will hopefully be implemented globally so that no lives are under danger. Car racing is a global sport so our product will definitely have an impact. Not only is global safety being addressed, but we hope that our auto-generation of stream will capture races in a more timely and accurate manner, to enhance the experience of the global audience.

Part B was written by Thomas Li

The multi-camera live-streaming system we design seeks to meet the cultural needs of today’s car sports enthusiasts, specifically F1 racing culture. Primarily, we do this by  providing the viewing experience already established among fans as optimal through algorithmic feed selection. There is already a culture established by race casters, real cameramen, racers, and viewers that we will analyze to determine this optimal viewing experience.

Part C was written by Bhavya Jain

Given our system of cameras closely mirrors that which already exists (with the addition of automated movement, and software for automated feed construction) there seem to be no glaring environmental factors that we feel we must consider. The movement of the cameras will consume some power that was previously a physical force and overall running of the system will consume some power. Motor racing is a very demanding sport in terms of material and power requirements, but our system does not add any significant pressure to these requirements.

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Jae’s Status Report for 3/9/24

Most of last week was spent on working on the design document. First, since we switched topics a week before the design doc was due, I came up with new use-case requirements and met up with our TA to finalize them. She also helped me draft some good design requirements that I hadn’t thought of before. While working on the design doc, we were able to make good progress in finalizing our design for the project. I worked on abstract, use-case requirements, architecture, design trade studies (hardware), system implementation (hardware), summary, team member responsibilities, and reach goals.

After design document was submitted, I spent some of the spring break on Arduino code. Specifically, the communication between the object tracking module of OpenCV and the motor control through Arduino. I found a way to use serial monitor of Arduino to serially send and receive data from the PC. I am able to control the movement of the motors with a simple python code. Although the interface seems to be working, I have not tested it yet with Bhav’s object tracking module so that is my next task in hand.

On schedule, my progress is slightly off. I was supposed to work on camera distance and location determination, but instead I worked on the code which is next week’s task. So I’m not too behind on schedule.

Next week, I hope to have the code finished, determine camera stand locations, and start assembling the camera stands.