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Prosopagnosia
Published in Alexander R. Toftness, Incredible Consequences of Brain Injury, 2023
Facial recognition is seemingly automatic in many people, but some struggle to recognize identities from faces. Prosopagnosia was named in 1947, when Joachim Bodamer wrote about some patients that had problems identifying who was in a given photograph. For example, one of the patients, when shown a picture of a dog, thought that it was a picture of a person, but with “curious hair” (Bodamer, 1947, as discussed in Bornstein et al., 1969, p. 164). He named this disorder “prosop agnosia” from the Greek words for “face ignorance.” In popular culture, prosopagnosia is often called face blindness, which is much easier to say. The disorder made some appearances in a few episodes of the television show Arrested Development and was depicted more or less accurately, except perhaps for the scene in which Tobias is mistaken as Lindsay (Lorey et al., 2013). People with prosopagnosia often complain about being unable to follow the storyline of television shows and films because they have trouble telling the actors apart, so they would probably find that face-blindness plot from Arrested Development to be quite confusing (e.g., Bowles et al., 2009).
Consumer-Grade Cameras and Other Approaches to Surface Imaging
Published in Jeremy D. P. Hoisak, Adam B. Paxton, Benjamin Waghorn, Todd Pawlicki, Surface Guided Radiation Therapy, 2020
The Kinect API allows for more than just raw point cloud data to be acquired. Computer vision capabilities are also embedded in both the hardware and the software system which allows the parsing of estimated skeletal positions and facial features. Both of these functions have been exploited and applied to radiation therapy needs. Silverstein et al. demonstrated a rudimentary facial recognition system for verifying patient identity prior to treatment.12 The system relied on the Kinect API to provide 31 unique facial points from the subject’s surface scan. From these points, the distance between each pair of points was calculated to create a vector array unique to each patient’s face. Using just the mean and median differences between two scanned vector arrays, the discrimination of identity could be obtained (sensitivity 96.5%, specificity 96.7%). The authors did note that the results were highly dependent on lighting conditions. Another use of the Kinect was by Mullaney et al. in which they demonstrated patients could be allowed to participate in their positioning.13 In their prototype example, the depth sensors parsed the patient joint locations and the patients watched a display showing the desired and current position of their joints. A feedback system, consisting of a simple user interface, was used to positively validate the correct position in a user interface.
Artificial vision and retinal prostheses
Published in A Peyman MD Gholam, A Meffert MD Stephen, D Conway MD FACS Mandi, Chiasson Trisha, Vitreoretinal Surgical Techniques, 2019
Humayun Mark S, Lakhanpal Rohit R, Weiland James D
Studies simulating electrodes placed over the entire macula rather than a foveal pixelization have assessed the ability of subjects to recognize faces through a pixilated square grid. Parameters included grid size (10° [H11003] 10 to 32° [H11003] 32 dots), dot size, gap width, dot dropout rate, and grayscale resolution. The subjects achieved highly significant facial recognition accuracies in both high- and low-contrast tests, with a marked learning effect being documented. These results suggest that reliable facial recognition is possible even with crude visual prostheses, and possibly makes the task of engineering the implant easier as it would require fewer data/stimulation channels.21 The ability of subjects to read using a pixilated visual simulator has been evaluated in a separate cohort, which demonstrated that most subjects are able to read fonts as small as 36-point (and all could read 57-point) using a 16 × 16 pixel array.22,23
Security cameras in taxicabs with three rows of seating
Published in International Journal of Occupational Safety and Ergonomics, 2022
The test procedures were designed to evaluate the camera resolution of sample security cameras in the third-row seats of a simulated three-row-seating taxicab for their compliance with the minimum camera resolution requirements. Five sample taxicab security cameras with different image-sensor pixel counts, mounted on the windshield or the ceiling of the simulated taxicab, recorded in-cab images with a specially designed normalized camera resolution test chart mounted in a third-row seat. The camera resolution compliance was tested in two extreme light conditions, bright sunny daylight and dark conditions with infrared (IR) light-emitting diode (LED) radiation. In the post-test data analysis, the test chart images were retrieved from the captured cab images and the camera resolution was measured by photographic quality test software. Each measured camera resolution was compared with the camera resolution requirement for customer facial identification, which was determined in a previous taxicab security camera study [5]. The camera resolution was also compared with the camera resolution threshold for computer facial recognition.
The neuropsychological rehabilitation of visual agnosia and Balint’s syndrome
Published in Neuropsychological Rehabilitation, 2019
Joost Heutink, Dana L. Indorf, Christina Cordes
Both literature reviews concluded that restorative training has not yet proven to be very successful and that compensatory strategies appeared to be a more effective approach for the rehabilitation of acquired prosopagnosia (Bate & Bennetts, 2014; DeGutis, Chiu, Grosso, & Cohan, 2014). The additional eight articles appeared to be in line with the outcome of the literature reviews, especially with regard to transferring the training to real-life face recognition (Bate et al., 2015). The study by Davies-Thompson et al. (2017) describes a promising restorative approach, however training is very intense and does not improve real-life facial recognition in all participants involved. Concluding, compensation strategies seemed to be most promising for the rehabilitation of prosopagnosia.
Evaluation and prediction of polygon approximations of planar contours for shape analysis
Published in Journal of Applied Statistics, 2018
Chalani Prematilake, Leif Ellingson
The expansion of technology over the past few decades has brought with it tremendous amounts of digital imaging data arising in a variety of fields. Perhaps most visibly, even standard digital cameras are capable of producing images that are suitable for use in a number of applications related to computer vision, including scene recognition and facial recognition. Additionally, advances in health-care have led to a rapid growth in medical imaging technology. Among the many types of medical images are X-rays and computed tomography scans. When working with such data, researchers are typically concerned with certain features of an image rather than the entire image, itself. Often, the feature of interest is the shape of the outline of an object depicted in the image, as discussed in Osborne [34] and Qiu et al. [37].