Text grammar (morphology/syntax), type (narrative = easier), and speaker gender (female = easier) and profession (philology professor = harder) affect difficulty in sentence segmentation. #LingCologne
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Last night I was playing a little with Openpose data in #RStats. I realized it's not too hard to wrangle the Openpose output and plot signing directly using #ggplot2 and #gganimate, like so:
But I decided to make some tweaks so you can change the color of the signer+clothes, which makes seeing the hands a bit easier (contrast!)...
But also, why not give your signer a pretty turtleneck to wear?
You guys know that IKEA products are basically just #Swedish words and place names, right? Walking around an IKEA store is like walking through a dictionary.
This is a script simulating the idea in Swedish and other places/languages: github.com/borstell/fakea
So you can now input a video and it outputs it slower and/or repeated. Here's an example of a sign for 'deaf' in STS rendered with a repeated 30% speed playback!
(Oh, and passed to the make_gif() function as well!)
And the automatic face blurring works great! Even with multiple people in the image (or, like here, multiple repetitions of the same person in one composite image)!
So, it's like *very* easy to process and reconstruct actual images with only a few lines of code. As in plotting software redrawing the image, pixel by pixel.
Here's is a gif of me made with #ggplot2 and #gganimate. Sunday = fun day!