Computerized feature systems for identifying suspects: empirical tests using crime scenarios

摘要

When a witness in a criminal investigation is asked to identify a suspect in a conventional, randomly ordered album of photographs, identification success deteriorates rapidly as more photos are examined. An alternative is a feature-based retrieval system in which mug shots of previous offenders are displayed in order of similarity to a witness's description of a suspect's facial features. Previous studies have shown that the use of a feature system increases identification success by reducing the number of photographs witnesses examine. However, those studies failed to test feature systems in naturalistic settings. Two experiments are reported showing that feature systems are, indeed, effective in more naturalistic settings. In one, subject witnesses viewed a 37-second videotape of a crime in progress. In the other, they witnessed a live confrontation between two people. Afterwards, witness descriptions of the facial features of each suspect were compared with those of 1000 official police mug shots on file. The number of photos to be examined to find target suspects was reduced from the 500 expected for the traditional album to an average of less than 25.