izpis_h1_title_alt

Upodabljanje umetnih sekvenc za vizualno sledenje
ID KUZMAN, LUKA (Author), ID Čehovin Zajc, Luka (Mentor) More about this mentor... This link opens in a new window

.pdfPDF - Presentation file, Download (19,78 MB)
MD5: C46889F7117D008F8FCA1564AA16FFDD

Abstract
V diplomski nalogi smo izdelali sistem za uporabljanje umetnih sekvenc, primernih za uporabo v vizualnem sledenju za vrednotenje ali učenje sledilnih algoritmov. Sistem je zasnovan kot razširitev za program za 3D modeliranje Blender in omogoča parametriziranje dinamike različnih lastnosti scen, npr. dinamike kamere, svetlobe. Tak način ustvarjanja sekvenc omogoča tudi hitro generiranje natančnih oznak, ki so potrebne za vrednotenje ali učenje. Za prikaz uporabnosti našega pristopa smo ustvarili pet scen iz katerih smo generirali 30 sekvenc in na njih ovrednotili štiri referenčne sledilnike. S spreminjanjem parametrov sekvenc lahko demonstriramo določene omejitve posameznih sledilnikov, ki jih lahko povežemo z njihovo zasnovo.

Language:Slovenian
Keywords:vizualno sledenje, vrednotenje, parametrizacija, sintetične sekvence
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
FMF - Faculty of Mathematics and Physics
Year:2021
PID:20.500.12556/RUL-130809 This link opens in a new window
COBISS.SI-ID:78761219 This link opens in a new window
Publication date in RUL:17.09.2021
Views:1195
Downloads:132
Metadata:XML DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Secondary language

Language:English
Title:Rendering synthetic sequences for visual tracking
Abstract:
In this thesis, we have developed a system for creating synthetic sequences suitable for use in visual tracking to evaluate or learn tracking algorithms. The system is designed as an extension for the 3D modelling software Blender and allows for parametrisation of dynamics of different scene features, e.g. camera dynamics, lighting. This way of generating sequences also allows for quick generation of accurate labels needed for evaluation or learning. To demonstrate the applicability of our approach, we created five scenes using which we generated 30 sequences and evaluated four reference trackers on them. By changing the parameters of the sequences, we can demonstrate certain limitations of each tracker that can be linked to their design.

Keywords:visual tracking, evaluation, parametrisation, synthetic sequences

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back