Towards Similarity Models in Police Photo Lineup Assembling Tasks
The result's identifiers
Result code in 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>
Alternative codes found
RIV/00216208:11210/18:10378948
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Towards Similarity Models in Police Photo Lineup Assembling Tasks
Original language description
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' 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA17-22224S" target="_blank" >GA17-22224S: User preference analytics in multimedia exploration models</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Similarity Search and Applications
ISBN
978-3-030-02224-2
ISSN
1611-3349
e-ISSN
neuvedeno
Number of pages
9
Pages from-to
217-225
Publisher name
Springer International Publishing
Place of publication
Springer Nature Switzerland AG
Event location
Lima
Event date
Oct 7, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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