Correction: A survey of U.S. public perspectives on facial recognition technology and facial imaging data practices in health and research contexts

Facial imaging and facial recognition technologies, now common in our daily lives, also are increasingly incorporated into health care processes, enabling touch-free appointment check-in, matching patients accurately, and assisting with the diagnosis of certain medical conditions. The use, sharing, and storage of facial data is expected to expand in coming years, yet little is documented about the perspectives of patients and participants regarding these uses. We developed a pair of surveys to gather public perspectives on uses of facial images and facial recognition technologies in healthcare and in health-related research in the United States. We used Qualtrics Panels to collect responses from general public respondents using two complementary and overlapping survey instruments; one focused on six types of biometrics (including facial images and DNA) and their uses in a wide range of societal contexts (including healthcare and research) and the other focused on facial imaging, facial recognition technology, and related data practices in health and research contexts specifically. We collected responses from a diverse group of 4,048 adults in the United States (2,038 and 2,010, from each survey respectively). A majority of respondents (55.5%) indicated they were equally worried about the privacy of medical records, DNA, and facial images collected for precision health research. A vignette was used to gauge willingness to participate in a hypothetical precision health study, with respondents split as willing to (39.6%), unwilling to (30.1%), and unsure about (30.3%) participating. Nearly one-quarter of respondents (24.8%) reported they would prefer to opt out of the DNA component of a study, and 22.0% reported they would prefer to opt out of both the DNA and facial imaging component of the study. Few indicated willingness to pay a fee to opt-out of the collection of their research data. Finally, respondents were offered options for ideal governance design of their data, as “open science”; “gated science”; and “closed science.” No option elicited a majority response. Our findings indicate that while a majority of research participants might be comfortable with facial images and facial recognition technologies in healthcare and health-related research, a significant fraction expressed concern for the privacy of their own face-based data, similar to the privacy concerns of DNA data and medical records. A nuanced approach to uses of face-based data in healthcare and health-related research is needed, taking into consideration storage protection plans and the contexts of use.

Download Full-text

Facial Recognition From Volume-Rendered Magnetic Resonance Imaging Data

IEEE Transactions on Information Technology in Biomedicine ◽

10.1109/titb.2008.2003335 ◽

2009 ◽

Vol 13 (1) ◽

pp. 5-9 ◽

Cited By ~ 21

Author(s):

F.W. Prior ◽

B. Brunsden ◽

C. Hildebolt ◽

T.S. Nolan ◽

M. Pringle ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Facial Recognition ◽

Imaging Data ◽

Resonance Imaging ◽

Magnetic Resonance Imaging Data

Download Full-text

Facial Recognition from Volume Rendered Magnetic Resonance Imaging Data

IEEE Transactions on Information Technology in Biomedicine ◽

10.1109/titb.2008.2007672 ◽

2009 ◽

Author(s):

F. Prior ◽

B. Brunsden ◽

C. Hildebolt ◽

T. Nolan ◽

M. Pringle ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Facial Recognition ◽

Imaging Data ◽

Resonance Imaging ◽

Magnetic Resonance Imaging Data

Download Full-text

How to Govern Visibility?: Legitimizations and Contestations of Visual Data Practices after the 2017 G20 Summit in Hamburg

Surveillance & Society ◽

10.24908/ss.v18i4.13535 ◽

2020 ◽

Vol 18 (4) ◽

pp. 522-539

Author(s):

Rebecca Venema

Keyword(s):

Facial Recognition ◽

Qualitative Content Analysis ◽

Social Contexts ◽

Social Consequences ◽

Public Realm ◽

Visual Data ◽

Parliamentary Debates ◽

Data Practices ◽

Visual Technologies ◽

Blind Spots

Technological changes shift how visibility can be established, governed, and used. Ubiquitous visual technologies, the possibility to distribute and use images from heterogeneous sources across different social contexts and publics, and increasingly powerful facial recognition tools afford new avenues for law enforcement. Concurrently, these changes also trigger fundamental concerns about privacy violations and all-encompassing surveillance. Using the example of police investigations after the 2017 G20 summit in Hamburg, the present article provides insights into how different actors in the political and public realm in Germany deal with these potentials and tensions in handling visual data. Based on a qualitative content analysis of newspaper articles (n=42), tweets (n=267), experts’ reports (n=3), and minutes of parliamentary debates and committee hearings (n=8), this study examines how visual data were collected, analyzed, and published and how different actors legitimated and contested these practices. The findings show that combined state, corporate, and privately produced visual data and the use of facial recognition tools allowed the police to cover and track public life in large parts of the inner city of Hamburg during the summit days. Police authorities characterized visual data and algorithmic tools as objective, trustworthy, and indispensable evidence-providing tools but black-boxed the heterogeneity of sources, the analytical steps, and their potential implications. Critics, in turn, expressed concerns about infringements of civic rights, the trustworthiness of police authorities, and the extensive police surveillance capacities. Based on these findings, this article discusses three topics that remained blind spots in the debates but merit further attention in discussions on norms for visual data management and for governing visibility: (1) collective responsibilities in visibility management, (2) trust in visual data and facial recognition technologies, and (3) social consequences of encompassing visual data collection and registered faceprints.

Download Full-text

Correlation of Pore Structure and Permeability by SEM-Image Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100180896 ◽

1990 ◽

Vol 48 (1) ◽

pp. 428-429

Author(s):

C. A. Callender ◽

Wm. C. Dawson ◽

J. J. Funk

Keyword(s):

Image Analysis ◽

Pore Structure ◽

Imaging System ◽

Pore Space ◽

Simulation Models ◽

Image Analyzer ◽

Imaging Data ◽

Sem Images ◽

Thin Sections ◽

Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

Download Full-text

Perceptual Effects and Recollective Experience in Face Recognition

Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) ◽

10.1027/1618-3169.52.3.224 ◽

2005 ◽

Vol 52 (3) ◽

pp. 224-231 ◽

Cited By ~ 7

Author(s):

Chrisanthi Nega

Keyword(s):

Face Recognition ◽

Recognition Memory ◽

Congruency Effect ◽

Facial Recognition ◽

Memory Systems ◽

Study Time ◽

Perceptual Fluency ◽

Recollective Experience ◽

Trace Strength ◽

Size Congruency

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.

Download Full-text