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Shiheng’s Status Report for 11/18/2023

My work this week reflects the efforts I made on the backend on integration with Ray and continued progress in implementing vocal instructions.

I have been actively driving progress in the project, specifically focusing on enabling pose selection from multiple persons. My work involves extensive Python scripting to develop a flexible system that is automated to choose poses from different individuals and pick out the Taichi practitioner. User will be able to train in environment not so private (e.g. gyms) without the need of having the room cleared to prevent the system from capturing other body parts.

Additionally, I have taken on the responsibility of building the backend support for skeleton drawing. Through passing angles with a reference frame, I enabled Ray to pinpoint and draw the vectors for the reference skeleton. The user skeleton follows the similar logic, and I have lay down the foundation for comparison through passing a boolean list for verfication purposes and creating visual cues on the front end.

I am still working and researching on creating good vocal instructions while putting the sequence and body parts priority in mind, which should be done by the end of this weekend and ready for testing. For following weeks, I will focus on testing and fixing bugs from our final product with all the functions done.

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Team Status Report for 11/18/2023

As we are approaching the end of semester, our team worked on integration and finetuning the infrastructure for the upcoming testing and verfication.

Jerry has been focused on enhancing the user experience by introducing custom pose sequence support. He’s also succeeded in integrating the app with file manager to handle multiple files, providing users with an efficient way to manage their custom pose uploads. Additionally, Jerry has improved user interaction by enabling the removal and reordering of files to be uploaded, directly within the app’s display.

Shiheng has taken on the challenge of allowing pose selection from multiple persons, a crucial feature for users within more complex environments and handling different outputs when multiple bodies are found in frame. In addition, he is concentrating on backend support for skeleton drawing for Ray, implementing a new and different approach for measuring angles that could be handled better on the frontend without the need for processing the raw data from Openpose.

Hongzhe (Eric) is dedicated to refining the visual aspects of the application. His work involves processing reference images to enhance their display quality. He is also focusing on establishing parameter connections, which will contribute to a more cohesive and user-friendly experience. Additionally, Hongzhe is also involved in fine-tuning the logic on the training page to ensure an optimized user journey.

Ray is playing a pivotal role in consolidating the efforts of the team. He is synthesizing key points and reference angles provided by Shiheng into the overall skeleton drawing process. Ray is also leading the redesign of UI components for improved aesthetics and usability, working on cleaning up the code and optimization. Furthermore, he is involved in refactoring reference pictures to enhance user experience with bigger picture components for better feedback experience.

ABET Question (How we have grown as a team?):

Throughout the semester, our team has experienced substantial growth and cohesion. We have established a robust framework for collaboration and decision-making, utilizing Google Drive for weekly reports, design documents, Github repo for codes, and Slack channel for communication and collaboration efforts.

Our mandatory lab sessions on Mondays and Wednesdays have provided consistent opportunities for team members to discuss progress and align our efforts. Additionally, our Friday or Saturday sessions over zoom have been dedicated to refining plans and syncing up progress during the week.

The use of Gantt Charts has proven instrumental in visualizing our project timeline and ensuring that tasks are allocated efficiently. This strategic planning has allowed us to stay on track and adapt to unforeseen challenges effectively. By regularly revisiting and adjusting our goals based on progress and feedback, we have fostered a dynamic and adaptive team culture.

Our commitment to an open and inclusive environment has been foundational to our success. We actively seek input from all team members, ensuring that each voice is heard and valued. Though we faced changes in group composition and change of plan in the beginning of the semester, everyone in the group was equally treated.

Thanks to everyone’s effort in creating an equal and exclusive environment, we have been able to make substantial progress from scratch as a group and advance through the hardships we faced throughout the semester.

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Hongzhe’s Status Report for Week 11/18/2023

For this week, we are trying our best to finalize all the functionality portion of the project given there is no scheduled task from the course schedule.

Personally, in charge of integration, I did a lot of communication all over the team to finalize the details for each part. We came up with the idea that since users need more distance in order to be fully captured by the built-in camera (assuming they are not buying another one), the training screen needs to be reformatted so that all visual data could be better seen. Thus, I manually reprocessed all the reference poses. At the same time, I was able to work with Ray to finish the settings page, where we use scroll bars to control setting parameters such as pre-train hold duration etc. I am working on a different logic for the training page and get front support with Ray to change the way users start and end the training/instruction procedure, avoiding redundant position changes to access their PC.

For the next week during Thanksgiving, we will try our best to finish the application and move on to schedule interviews and start organizing verification.

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Ray’s Status Report for 11/18/2023

This week, our team mainly worked on frontend/backend integration, and I took most of my time working on the skeleton draw functionality.

In order to make our system as intuitive as possible, we will have a screen showing direct comparison between the reference pose and the user pose on the training page of our application. Specifically, we want to draw the skeleton of the reference pose and then overlay the user pose on top of it, so that the user can intuitively see which of their limbs have incorrect angles.

I implemented the algorithm for drawing the reference skeletonthis week. It’s much harder than I expected since I need to conducts a couple of transforms on the data derived from openpose. The coordinate system of openpose is very different from Kivy’s, and I need to find a way to center the drawn skeleton. Also, to process the data outputed from the backend, I read through the entire backend code and pointed out a few places where the naming of the variables does not fully represent what they are. For now, the drawn reference skeleton looks good, and I will attempt the drawing of the user skeleton this weekend.

Also, in order to maximize the portion of screen used so that users can see their poses from far away, I changed the formatting of the training screen, which now has the look shown by the image above.

Meanwhile, I also helped a bit with Jerry’s frontend pose sequence task where we both tried to understand how relative layout works.

I think we are still on schedule with our project and our application is in good shape. Still, we will probably need the thanksgiving break to fully integrate the system and test out the bugs. After finising the skeleton drawing algorithm, I will help Jerry work on the pose sequence functionality.