Using Causal Induction in Humans to Learn and Infer Causality from Video

@inproceedings{Fire2013UsingCI,
  title={Using Causal Induction in Humans to Learn and Infer Causality from Video},
  author={Amy Sue Fire and Song-Chun Zhu},
  booktitle={CogSci},
  year={2013}
}
Noisy Data: Increasing Misdetections Discussion: • Our method matches human perceptions in the presence of multiple confusing events. • In the presence of confounders (the monitor), our method appropriately reduces clarity in the causal relationships. • Our method incorporates dependencies in action hierarchies (the locked door). • Our method places importance on quantity of hits (the elevator), accommodating the ambiguity important to vision. • Clean detections are important to being able to… CONTINUE READING
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