Towards Similarity Models in Police Photo Lineup Assembling Tasks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10378948" target="_blank" >RIV/00216208:11320/18:10378948 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11210/18:10378948

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-02224-2_17" target="_blank" >https://doi.org/10.1007/978-3-030-02224-2_17</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-02224-2_17" target="_blank" >10.1007/978-3-030-02224-2_17</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards Similarity Models in Police Photo Lineup Assembling Tasks

Popis výsledku v původním jazyce

Photo lineups play a significant role in the eyewitness identification process. Lineups are used to provide evidence in the prosecution and subsequent conviction of suspects. Unfortunately, there are many cases where lineups have led to the incorrect identification and conviction of innocent suspects. One of the key factors affecting the incorrect identification is the lack of lineup fairness, i.e. that the suspect differs significantly from other candidates. Although the process of assembling a fair lineup is both highly important and time-consuming, only a handful of tools are available to simplify the task. In this paper, we follow our previous work in this area and focus on defining and tuning the inter-person similarity metric that will serve as a base for a lineup candidate recommender system. This paper proposes an inter-person similarity metric based on DCNN descriptors of candidates&apos; photos and their content-based features, which is further tuned by the feedback of domain experts. The recommending algorithm further considers the need for uniformity in lineups. The proposed method was evaluated in a realistic user study focused on lineup fairness over solutions proposed by domain experts. Results shown indicate that the precision of the proposed method is similar to the solutions proposed by domain experts and therefore the approach may significantly reduce the amount of manual work needed for assembling photo lineups.

Název v anglickém jazyce

Towards Similarity Models in Police Photo Lineup Assembling Tasks

Popis výsledku anglicky

Photo lineups play a significant role in the eyewitness identification process. Lineups are used to provide evidence in the prosecution and subsequent conviction of suspects. Unfortunately, there are many cases where lineups have led to the incorrect identification and conviction of innocent suspects. One of the key factors affecting the incorrect identification is the lack of lineup fairness, i.e. that the suspect differs significantly from other candidates. Although the process of assembling a fair lineup is both highly important and time-consuming, only a handful of tools are available to simplify the task. In this paper, we follow our previous work in this area and focus on defining and tuning the inter-person similarity metric that will serve as a base for a lineup candidate recommender system. This paper proposes an inter-person similarity metric based on DCNN descriptors of candidates&apos; photos and their content-based features, which is further tuned by the feedback of domain experts. The recommending algorithm further considers the need for uniformity in lineups. The proposed method was evaluated in a realistic user study focused on lineup fairness over solutions proposed by domain experts. Results shown indicate that the precision of the proposed method is similar to the solutions proposed by domain experts and therefore the approach may significantly reduce the amount of manual work needed for assembling photo lineups.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA17-22224S" target="_blank" >GA17-22224S: Analytika uživatelských preferencí v modelech multimediální explorace</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Similarity Search and Applications

ISBN

978-3-030-02224-2

ISSN

1611-3349

e-ISSN

neuvedeno

Počet stran výsledku

9

Strana od-do

217-225

Název nakladatele

Springer International Publishing

Místo vydání

Springer Nature Switzerland AG

Místo konání akce

Lima

Datum konání akce

7. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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