Abstrakt
In this paper we focus on the problem of assembling unbiased photo lineups. Photo lineups are an important method in the identification process for the prosecution and possible conviction of suspects.
Incorrect lineup assemblies have led to the false identification and conviction of innocent persons. One of the significant errors which can occur is the lack of lineup fairness, i.e., that the suspect significantly differs from other candidates.
Despite the importance of the task, few tools are available to assist police technicians in creating lineups. Furthermore, these tools mostly focus on fair lineup administration and provide only a little support in the candidate selection process.
In our work, we first summarize key personalization and information retrieval (IR) challenges of such systems and propose an IR/Personalization model that addresses them. Afterwards, we describe a LineIT tool that instantiate this model and aims to support police technicians in assembling unbiased lineups.