Pregled bibliografske jedinice broj: 450951
Self-adaptive Vision System
Self-adaptive Vision System // Emerging Trends in Technological Innovation. IFIP Advances in Information and Communication Technology / Camarinha-Matos, Luis M. ; Pereira Pedro ; Ribeiro Luis (ur.).
Heidelberg: Springer, 2010. str. 195-202 doi:10.1007/978-3-642-11628-5_21 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 450951 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Self-adaptive Vision System
Autori
Stipančić, Tomislav ; Jerbić, Bojan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Emerging Trends in Technological Innovation. IFIP Advances in Information and Communication Technology
/ Camarinha-Matos, Luis M. ; Pereira Pedro ; Ribeiro Luis - Heidelberg : Springer, 2010, 195-202
ISBN
978-3-642-11627-8
Skup
Doctoral Conference on Computing, Electrical and Industrial Systems
Mjesto i datum
Costa de Caparica, Portugal, 22.02.2010. - 24.02.2010
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
active vision system ; self adaptation ; active behavioral scheme ; experiment planning ; response surface methodology
Sažetak
Light conditions represent an important part of every vision application. This paper describes one active behavioral scheme of one particular active vision system. This behavioral scheme enables an active system to adapt to current environmental conditions by constantly validating the amount of the reflected light using luminance meter and dynamically changed significant vision parameters. The purpose of the experiment was to determine the connections between light conditions and inner vision parameters. As a part of the experiment, Response Surface Methodology (RSM) was used to predict values of vision parameters with respect to luminance input values. RSM was used to approximate an unknown function for which only few values were computed. The main output validation system parameter is called Match Score. Match Score indicates how well the found object matches the learned model. All obtained data are stored in the local database. By timely applying new parameters predicted by the RSM, the vision application works in a stabile and robust manner.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Računarstvo, Strojarstvo
POVEZANOST RADA
Projekti:
MZOS-120-1201948-1941 - AUTONOMNA VIŠEAGENTNA AUTOMATSKA MONTAŽA (Jerbić, Bojan, MZOS ) ( CroRIS)
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb