Row 17407

Row ID: 17407 | Dataset Entry | Axioma AXP Content Repository

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FWIW, I eventually found [this](https://www.sciencedirect.com/science/article/pii/S2468227620302039#:~:text=Micro%2Dexpressions%20are%20characterized%20by,and%20saves%20time%20and%20resources), which is an ML implementation of reading micro-expressions, which is the foundation of the original real-world research that Lie to Me was inspired by.

I need to read through it all the way, but it looks like you **can** read micro-expressions if you have a high-enough FPS camera. First glance is that normal facial recognition works, so long as you capture the frame containing the expression. The problem I would still have is, what does each micro-expression (supposedly) indicate? Are they even independent of context? And that's assuming they even last a consistent amount of time, so that I can create a time boundary for what's a normal expression and what's a micro-expression, but I digress...

FieldValue
text FWIW, I eventually found [this](https://www.sciencedirect.com/science/article/pii/S2468227620302039#:~:text=Micro%2Dexpressions%20are%20characterized%20by,and%20saves%20time%20and%20resources), which is an ML implementation of reading micro-expressions, which is the foundation of the original real-world research that Lie to Me was inspired by. I need to read through it all the way, but it looks like you **can** read micro-expressions if you have a high-enough FPS camera. First glance is that n…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-20
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{
  "text": "FWIW, I eventually found [this](https://www.sciencedirect.com/science/article/pii/S2468227620302039#:~:text=Micro%2Dexpressions%20are%20characterized%20by,and%20saves%20time%20and%20resources), which is an ML implementation of reading micro-expressions, which is the foundation of the original real-world research that Lie to Me was inspired by. \n\nI need to read through it all the way, but it looks like you **can** read micro-expressions if you have a high-enough FPS camera. First glance is that normal facial recognition works, so long as you capture the frame containing the expression. The problem I would still have is, what does each micro-expression (supposedly) indicate? Are they even independent of context? And that's assuming they even last a consistent amount of time, so that I can create a time boundary for what's a normal expression and what's a micro-expression, but I digress...",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-20",
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