diplomsko delo
Robert Ravnik (Author), Franc Solina (Mentor)

Abstract

Digitalna karakterizacija z uporabo računalniškega vida v realnem času

Keywords

digitalno oglaševanje;digitalna karakterizacija;računalniški vid;klasifikacija spola;računalništvo;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [R. Ravnik]
UDC: 004.93(043.2)
COBISS: 7151700 Link will open in a new window
Views: 20
Downloads: 0
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Other data

Secondary language: English
Secondary title: [Digital characterization using computer vision in real-time]
Secondary abstract: A computer system for digital characterization is described. It is an intelligent system for displaying selected visual information on a computer screen. The system tracks and characterizes the viewers by analyzing the images of their faces taken by a camera attached to the screen, using the computer vision methods in real time. It also performs logging and analysis of recorded data. Main components of the system are the player and the main server. The player performs characterization of the viewers which can be used for adjusting the information on the screen. The main server performs selection of the presented information and manipulates the data. The problem of face detection and tracking is solved by applying the methods of AdaBoost and Lucas-Kanade optical flow. Detection and tracking of several observers is performed in real time. In face characterization we use the Principal Component Analysis (PCA) and the data mining environment Orange. Characterization of the observer's gender from their face is specially treated. The following methods of machine learning are applied and inter-compared in the Orange environment: naive Bayes, K-nearest neighbors, classification tree and random forest. A part of FERET face image library is used as learning and test sets. Selected methods are implemented for real time application on a PC. Gender of an observer can be determined in 17,9 ms with 83,3% reliability using random forest classifier. A web application for managing of the system and for generating reports is developed, including statistical analysis and visualization of data.
Secondary keywords: digital signage;digital characterization;computer vision;gender classification;computer science;diploma;
File type: application/pdf
Type (COBISS): Undergraduate thesis
Thesis comment: Univerza v Ljubljani, Fakulteta za računalništvo in informatiko
Pages: 56 str.
ID: 23868197