I have a partly developed, golf-related video analysis application currently written in the R and Shiny languages (partly because they were supposed to be quicker and/or easier for a first version, though this has turned out to be anything but). While the present intent is to get this application running as a web application as soon as possible, desktop and/or mobile versions will likely ultimately be needed also. So the best programming language(s) or platform(s) can be recommended for these.
The application does not have to continue in R. In fact, it currently runs extremely slowly, has other issues (not known if language or programmer issues), and might have to be rewritten anyhow even if initially successfully formulated in R. (There are some nice visuals within this R application, and I do not know if they can be comparatively duplicated in any other languages). Others have often suggested Python, C++, and/or OpenCV, but different languages have also been suggested.
Users start by recording videos of their golfing pre-swing motions (which could last as much as 15 seconds or more). A selected video is uploaded (if web based) into the application. The original video format (which could vary) is reformatted (to MP4 at this time I think), and frame numbers are added (time code could be used instead if deemed more efficient).
The reformatted video is next analyzed essentially frame by frame (forward and backward needed). This can currently be done somewhat decently in certain browsers, but not at all in others (not good). So an option currently exists for downloading the reformatted video for analysis in a local video player. One or more shorter segments of the video are selected to be further analyzed. The determined segment(s) is input into an analysis section of the application, and specified visual and mathematical parameters are computed and output.
What needs to be accurately tracked and analyzed is the pre-swing golf club movement (before a swing even begins). This has been done in the application by a color-tracking computer vision program, with the program marking and tracking two colored markers placed at known club positions before recording a video.
The auto-tracking feature is great and needed, yet rarely 100% correct in placing tracking markers (even for video segments comprising as few as ten frames). A feature for reviewing marker placements is also included and needed. A strictly manual marker placement is problematical, as even very short (time-wise) video segments can have high frame rates and be much too cumbersome to mark all frames manually.
So some type of "hybrid" tracking system would seem to be in order, consisting of an auto-tracking system coupled with a supplemental feature for reviewing and manually altering auto-placed markers as needed. This has not been satisfactorily achieved yet, thus data from the analysis section of the application has little value to this point.
Based on working with the partially developed application, I am confident that an appropriately skilled contractor using an appropriate language or platform should be able to achieve a superbly operating application without much difficulty, further time, and expense. In light of this and while I am open to something like Artificial Intelligence or machine learning video tracking, it would have to be done at a comparable time and cost of the color-tracking system presently used.
This project is already beyond the point of desperation. It needs to be running successfully as soon as possible (and at as little additional cost as possible at least until successful operation is proven). I please need help to successfully complete the development of the application and deploy it online. Hourly or project rates can be considered. A more detailed description is available for examination, but a simple statement will be needed first that all information will be kept confidential. Thank you very much.
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Hello, dear sir I am expert in matlab I have a lot of experiences in many golfer video analysis tasks. I will help you well. Please contact me. thanks