Criminal investigations often use photographic evidence to identify suspects. Here we combined robust face perception and high-resolution photography to mine face photographs for hidden information. By zooming in on high-resolution face photographs, we were able to recover images of unseen bystanders from reflections in the subjects' eyes. To establish whether these bystanders could be identified from the reflection images, we presented them as stimuli in a face matching task (Experiment 1). Accuracy in the face matching task was well above chance (50%), despite the unpromising source of the stimuli. Participants who were unfamiliar with the bystanders' faces (n = 16) performed at 71% accuracy [t(15) = 7.64, p<.0001, d = 1.91], and participants who were familiar with the faces (n = 16) performed at 84% accuracy [t(15) = 11.15, p<.0001, d = 2.79]. In a test of spontaneous recognition (Experiment 2), observers could reliably name a familiar face from an eye reflection image. For crimes in which the victims are photographed (e.g., hostage taking, child sex abuse), reflections in the eyes of the photographic subject could help to identify perpetrators.
BACKGROUND: Static posture, repetitive movements and lack of physical variation are known risk factors for work-related musculoskeletal disorders, and thus needs to be properly assessed in occupational studies. The aims of this study were (i) to investigate the effectiveness of a conventional exposure variation analysis (EVA) in discriminating exposure time lines and (ii) to compare it with a new cluster-based method for analysis of exposure variation. METHODS: For this purpose, we simulated a repeated cyclic exposure varying within each cycle between “low” and “high” exposure levels in a “near” or “far” range, and with “low” or “high” velocities (exposure change rates). The duration of each cycle was also manipulated by selecting a “small” or “large” standard deviation of the cycle time. Theses parameters reflected three dimensions of exposure variation, i.e. range, frequency and temporal similarity.Each simulation trace included two realizations of 100 concatenated cycles with either low (rho = 0.1), medium (rho = 0.5) or high (rho = 0.9) correlation between the realizations. These traces were analyzed by conventional EVA, and a novel cluster-based EVA (C-EVA). Principal component analysis (PCA) was applied on the marginal distributions of 1) the EVA of each of the realizations (univariate approach), 2) a combination of the EVA of both realizations (multivariate approach) and 3) C-EVA. The least number of principal components describing more than 90% of variability in each case was selected and the projection of marginal distributions along the selected principal component was calculated. A linear classifier was then applied to these projections to discriminate between the simulated exposure patterns, and the accuracy of classified realizations was determined. RESULTS: C-EVA classified exposures more correctly than univariate and multivariate EVA approaches; classification accuracy was 49%, 47% and 52% for EVA (univariate and multivariate), and C-EVA, respectively (p < 0.001). All three methods performed poorly in discriminating exposure patterns differing with respect to the variability in cycle time duration. CONCLUSION: While C-EVA had a higher accuracy than conventional EVA, both failed to detect differences in temporal similarity. The data-driven optimality of data reduction and the capability of handling multiple exposure time lines in a single analysis are the advantages of the C-EVA.
- Environmental health : a global access science source
- Published about 1 year ago
Lead (Pb) is a toxic substance with well-known, multiple, long-term, adverse health outcomes. Shooting guns at firing ranges is an occupational necessity for security personnel, police officers, members of the military, and increasingly a recreational activity by the public. In the United States alone, an estimated 16,000-18,000 firing ranges exist. Discharge of Pb dust and gases is a consequence of shooting guns.
Focal adjustment and zooming are universal features of cameras and advanced optical systems. Such tuning is usually performed longitudinally along the optical axis by mechanical or electrical control of focal length. However, the recent advent of ultrathin planar lenses based on metasurfaces (metalenses), which opens the door to future drastic miniaturization of mobile devices such as cell phones and wearable displays, mandates fundamentally different forms of tuning based on lateral motion rather than longitudinal motion. Theory shows that the strain field of a metalens substrate can be directly mapped into the outgoing optical wavefront to achieve large diffraction-limited focal length tuning and control of aberrations. We demonstrate electrically tunable large-area metalenses controlled by artificial muscles capable of simultaneously performing focal length tuning (>100%) as well as on-the-fly astigmatism and image shift corrections, which until now were only possible in electron optics. The device thickness is only 30 μm. Our results demonstrate the possibility of future optical microscopes that fully operate electronically, as well as compact optical systems that use the principles of adaptive optics to correct many orders of aberrations simultaneously.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 1 year ago
The power of visual imagery is well known, enshrined in such familiar sayings as “seeing is believing” and “a picture is worth a thousand words.” Iconic photos stir our emotions and transform our perspectives about life and the world in which we live. On September 2, 2015, photographs of a young Syrian child, Aylan Kurdi, lying face-down on a Turkish beach, filled the front pages of newspapers worldwide. These images brought much-needed attention to the Syrian war that had resulted in hundreds of thousands of deaths and created millions of refugees. Here we present behavioral data demonstrating that, in this case, an iconic photo of a single child had more impact than statistical reports of hundreds of thousands of deaths. People who had been unmoved by the relentlessly rising death toll in Syria suddenly appeared to care much more after having seen Aylan’s photograph; however, this newly created empathy waned rather quickly. We briefly examine the psychological processes underlying these findings, discuss some of their policy implications, and reflect on the lessons they provide about the challenges to effective intervention in the face of mass threats to human well-being.
The basis on which people make social judgments from the image of a face remains an important open problem in fields ranging from psychology to neuroscience and economics. Multiple cues from facial appearance influence the judgments that viewers make. Here we investigate the contribution of a novel cue: the change in appearance due to the perspective distortion that results from viewing distance. We found that photographs of faces taken from within personal space elicit lower investments in an economic trust game, and lower ratings of social traits (such as trustworthiness, competence, and attractiveness), compared to photographs taken from a greater distance. The effect was replicated across multiple studies that controlled for facial image size, facial expression and lighting, and was not explained by face width-to-height ratio, explicit knowledge of the camera distance, or whether the faces are perceived as typical. These results demonstrate a novel facial cue influencing a range of social judgments as a function of interpersonal distance, an effect that may be processed implicitly.
Two studies examined whether photographing objects impacts what is remembered about them. Participants were led on a guided tour of an art museum and were directed to observe some objects and to photograph others. Results showed a photo-taking-impairment effect: If participants took a photo of each object as a whole, they remembered fewer objects and remembered fewer details about the objects and the objects' locations in the museum than if they instead only observed the objects and did not photograph them. However, when participants zoomed in to photograph a specific part of the object, their subsequent recognition and detail memory was not impaired, and, in fact, memory for features that were not zoomed in on was just as strong as memory for features that were zoomed in on. This finding highlights key differences between people’s memory and the camera’s “memory” and suggests that the additional attentional and cognitive processes engaged by this focused activity can eliminate the photo-taking-impairment effect.
As bisexual individuals in the United States (U.S.) face significant health disparities, researchers have posited that these differences may be fueled, at least in part, by negative attitudes, prejudice, stigma, and discrimination toward bisexual individuals from heterosexual and gay/lesbian individuals. Previous studies of individual and social attitudes toward bisexual men and women have been conducted almost exclusively with convenience samples, with limited generalizability to the broader U.S.
The number of individuals with visual impairment (VI) and blindness is increasing in the United States and around the globe as a result of shifting demographics and aging populations. Tracking the number and characteristics of individuals with VI and blindness is especially important given the negative effect of these conditions on physical and mental health.
In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom-a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements.