scholarly journals Picturing Jonah Hill: memory-based image reconstruction of facial identity

2017 ◽  
Vol 17 (10) ◽  
pp. 249
Author(s):  
Chi-Hsun Chang ◽  
Dan Nemrodov ◽  
Andy Lee ◽  
Adrian Nestor
2017 ◽  
Author(s):  
Chi-Hsun Chang ◽  
Dan Nemrodov ◽  
Andy C. H. Lee ◽  
Adrian Nestor

AbstractVisual 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 opens the path to novel applications, such as computer-based ‘sketch artists’.


2014 ◽  
Vol 14 (10) ◽  
pp. 604-604 ◽  
Author(s):  
A. Nestor ◽  
D. Plaut ◽  
M. Behrmann

2017 ◽  
Vol 17 (10) ◽  
pp. 1262
Author(s):  
Dan Nemrodov ◽  
Matthias Niemeier ◽  
Ashutosh Patel ◽  
Adrian Nestor

eNeuro ◽  
2018 ◽  
Vol 5 (1) ◽  
pp. ENEURO.0358-17.2018 ◽  
Author(s):  
Dan Nemrodov ◽  
Matthias Niemeier ◽  
Ashutosh Patel ◽  
Adrian Nestor

2016 ◽  
Vol 16 (12) ◽  
pp. 1234
Author(s):  
Dan Nemrodov ◽  
Adrian Nestor ◽  
Galia Avidan ◽  
David Plaut ◽  
Marlene Behrmann

Author(s):  
R. A. Crowther

The reconstruction of a three-dimensional image of a specimen from a set of electron micrographs reduces, under certain assumptions about the imaging process in the microscope, to the mathematical problem of reconstructing a density distribution from a set of its plane projections.In the absence of noise we can formulate a purely geometrical criterion, which, for a general object, fixes the resolution attainable from a given finite number of views in terms of the size of the object. For simplicity we take the ideal case of projections collected by a series of m equally spaced tilts about a single axis.


Author(s):  
Santosh Bhattacharyya

Three dimensional microscopic structures play an important role in the understanding of various biological and physiological phenomena. Structural details of neurons, such as the density, caliber and volumes of dendrites, are important in understanding physiological and pathological functioning of nervous systems. Even so, many of the widely used stains in biology and neurophysiology are absorbing stains, such as horseradish peroxidase (HRP), and yet most of the iterative, constrained 3D optical image reconstruction research has concentrated on fluorescence microscopy. It is clear that iterative, constrained 3D image reconstruction methodologies are needed for transmitted light brightfield (TLB) imaging as well. One of the difficulties in doing so, in the past, has been in determining the point spread function of the system.We have been developing several variations of iterative, constrained image reconstruction algorithms for TLB imaging. Some of our early testing with one of them was reported previously. These algorithms are based on a linearized model of TLB imaging.


2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S678-S678
Author(s):  
Yasuhiro Akazawa ◽  
Yasuhiro Katsura ◽  
Ryohei Matsuura ◽  
Piao Rishu ◽  
Ansar M D Ashik ◽  
...  

1990 ◽  
Vol 137 (5) ◽  
pp. 351 ◽  
Author(s):  
C.P. Mariadassou ◽  
B. Yegnanarayana

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