Color-sketch simulator: a guide for color-based visual known-item search
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10366497" target="_blank" >RIV/00216208:11320/17:10366497 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-69179-4_53" target="_blank" >http://dx.doi.org/10.1007/978-3-319-69179-4_53</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-69179-4_53" target="_blank" >10.1007/978-3-319-69179-4_53</a>
Alternative languages
Result language
angličtina
Original language name
Color-sketch simulator: a guide for color-based visual known-item search
Original language description
In order to evaluate the effectiveness of a color-sketch retrieval system for a given multimedia database, tedious evaluations involving real users are required as users are in the center of query sketch formulation. However, without any prior knowledge about the bottlenecks of the underlying sketch-based retrieval model, the evaluations may focus on wrong settings and thus miss the desired effect. Furthermore, users have usually no clues or recommendations to draw color-sketches effectively. In this paper, we aim at a preliminary analysis to identify potential bottlenecks of a flexible color-sketch retrieval model. We present a formal framework based on position-color feature signatures, enabling comprehensive simulations of users drawing a color sketch.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
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/GA15-08916S" target="_blank" >GA15-08916S: Efficient subgraph discovery for petabyte-scale web analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advanced Data Mining and Applications
ISBN
978-3-319-69178-7
ISSN
0302-9743
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
754-763
Publisher name
Springer
Place of publication
Berlin
Event location
Singapore
Event date
Nov 5, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—