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See da4a0f0 for latest code changes on methodology. Current approach imitates this blog, repo link, which stores signs as a list of frames, where each frame is a list of all angles between every landmark on the hand. We then compute similarity between input video and a database of reference signs. Dynamic Time Warping allows for frames at different times in a video to be compared so that speed of signing is irrelevant.
If the last two are impossible with the DWT method, we can always switch to training a RNN or CNN for the task.
‼️Create PRs to merge functional code into the main repo. Only functioning code should be merged, but you should always push your latest developments to your own repo so that everyone else can view them and contribute.
The text was updated successfully, but these errors were encountered:
See da4a0f0 for latest code changes on methodology. Current approach imitates this blog, repo link, which stores signs as a list of frames, where each frame is a list of all angles between every landmark on the hand. We then compute similarity between input video and a database of reference signs. Dynamic Time Warping allows for frames at different times in a video to be compared so that speed of signing is irrelevant.
Our next steps are to:
If the last two are impossible with the DWT method, we can always switch to training a RNN or CNN for the task.
The text was updated successfully, but these errors were encountered: