Bodypressure – inferring body pose and contact pressure from a depth image

HIGHLIGHTS

• who: Henry M. Clever and collaborators from the intended to represent children, older adults, or people with medical conditions [77]Second, we used the SLP dataset, which consists of data from , participants (, female, male) recruited from undergraduate and graduate students at Northeastern University [3], [78]. Future research would benefit from more diverse populations. The GPU memory footprint of BPWnet is substantial. Reducing it may allow both Mod, and Mod, to be trained end-to-end, simplifying learning. Recent works in human body reconstruction provide other insights for boosting performance, including body-driven attention [79], structured prediction to . . .
  

   

  

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