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Memory and Perception-based Facial Image Reconstruction.

Chi-Hsun ChangDan NemrodovAndy C H LeeAdrian Nestor
Published in: Scientific reports (2017)
Visual memory for faces has been extensively researched, especially regarding the main factors that influence face memorability. However, what we remember exactly about a face, namely, the pictorial content of visual memory, remains largely unclear. The current work aims to elucidate this issue by reconstructing face images from both perceptual and memory-based behavioural data. Specifically, our work builds upon and further validates the hypothesis that visual memory and perception share a common representational basis underlying facial identity recognition. To this end, we derived facial features directly from perceptual data and then used such features for image reconstruction separately from perception and memory data. Successful levels of reconstruction were achieved in both cases for newly-learned faces as well as for familiar faces retrieved from long-term memory. Theoretically, this work provides insights into the content of memory-based representations while, practically, it may open the path to novel applications, such as computer-based 'sketch artists'.
Keyphrases
  • working memory
  • deep learning
  • big data
  • minimally invasive
  • soft tissue
  • optical coherence tomography
  • convolutional neural network
  • artificial intelligence