The facial recognition technology locks on once you’re in range. Benji Hutchinson works for NEC, a company that sells the software, gave CBS News a demonstration. “It’s putting the green box around us, and displaying our name,” Hutchinson said….
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‘Identikit-like system to reconstruct appearance of perps Richmond, Calif. “picture puzzles to put muggs in the jug.”‘
Public domain film from the Prelinger Archive, slightly cropped to remove uneven edges, with the aspect ratio corrected, and mild video noise reduction applied.
The soundtrack was also processed with volume normalization, noise reduction, clipping reduction, and/or equalization (the resulting sound, though not perfect, is far less noisy than the original).
A facial composite is a graphical representation of an eyewitness’s memory of a face, as recorded by a composite artist. Facial composites are used mainly by police in their investigation of (usually serious) crimes…
Construction of the composite was originally performed by a trained artist, through drawing, sketching, or painting, in consultation with a witness or crime victim. In the 1970s techniques were devised for use by those less artistically skilled, employing interchangeable templates of separate facial features, such as “Photofit” in the UK, Smith & Wesson’s “Identi-Kit” in the US and PortraitPad.
In the last two decades, a number of computer based facial composite systems have been introduced, amongst the most widely used systems are SketchCop FACETTE Face Design System Software, “Identi-Kit 2000”, FACES, E-FIT and PortraitPad. In the U.S. the FBI maintains that hand-drawing is its preferred method for constructing a facial composite. Many other police agencies, however, use software, since suitable artistic talent is often not available.
Until quite recently, the facial composite systems used by international police forces were exclusively based on a construction methodology in which individual facial features (eyes, nose, mouth, eyebrows, etc.) are selected one at a time from a large database and then electronically ‘overlaid’ to make the composite image. Such systems are often referred to as feature-based since they essentially rely on the selection of individual features in isolation. However, after a long period of research and development work conducted largely within British Universities, systems based on a rather different principle are finding increasing use by police forces. These systems may be broadly described as holistic or global in that they primarily attempt to create a likeness to the suspect through an evolutionary mechanism in which a witness’s response to groups of complete faces (not just features) converges towards an increasingly accurate image. Three such systems have come from academic beginnings, EFIT-V from the University of Kent, EvoFIT from Stirling and Central Lancashire University, and ID from the University of Cape Town, South Africa.
A general review of research into the evaluation of mechanical template techniques may be found in Davies and Valetine (2006) A review of research into more modern ‘feature’ and ‘recognition’ systems, and into methods for improving the effectiveness of composites, may be found in Frowd et al. (2008) and (2009).
The systems used in the UK have been subjected to a number of academic studies. These have typically shown that E-FIT and PRO-fit produce composites that are correctly named, either immediately or a few hours after construction, about 20% of the time (see Brace et al. (2000), Bruce et al. (2002), Davies et al. (2000) and Frowd et al. (2005)). When witnesses in these studies are required to wait two days before constructing a composite, which matches real use more closely, naming falls to a few percent at best (e.g. Frowd et al. (2005) and (2007)). The reason for the low level of naming from these systems appears to be that witnesses are unable to accurately construct the internal features of the face after long delays, the region that is important for recognition by another person later (Frowd et al. (2007)).
Evolutionary systems show a marked improvement in accuracy. In academic trials, research on a fairly-recent version of the EvoFIT system has shown correct naming levels of about 30% after a 2-day delay…
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