Semantic Apparatus – Recognising the dynamic form of fire

Cited by Lee Sonogan

1,711 Pop Art Fire Illustrations & Clip Art

Abstract by Fintan Nagle &Alan Johnston 

Encoding and recognising complex natural sequences provides a challenge for human vision. We found that observers could recognise a previously presented segment of a video of a hearth fire when embedded in a longer sequence. Recognition performance declined when the test video was spatially inverted, but not when it was hue reversed or temporally reversed. Sampled motion degraded forwards/reversed playback discrimination, indicating observers were sensitive to the asymmetric pattern of motion of flames. For brief targets, performance increased with target length. More generally, performance depended on the relative lengths of the target and embedding sequence. Increased errors with embedded sequence length were driven by positive responses to non-target sequences (false alarms) rather than omissions. Taken together these observations favour interpreting performance in terms of an incremental decision-making model based on a sequential statistical analysis in which evidence accrues for one of two alternatives. We also suggest that prediction could provide a means of providing and evaluating evidence in a sequential analysis model.

Publication: Scientific Reports (Peer-Reviewed Journal)

Pub Date: 19 May 2021 Doi: (Plenty more sections, figures and references in the article)

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