Augmented Reality and 3D modelling Done by Stafford Joemat Supervised by Mr James Connan

Project Overview Marker-based Augmented Reality uses a camera and a visual marker to determine the center of orientation and range of its coordinate system The system is effectively a driver that allows users to superimpose a 3D object on a predefined marker, across multiple frames using fixed input video source.

Project Overview Object Orientated Analysis  Grayscale  Speed Up Robust Features (SURF)  OpenGL Object Orientated Design User Interface Specification

Greyscale Fast image processing due to limited detail. Image intensity is stored in greyscale 8 bits per sampled pixel, which allows 256 different intensities Red, green, and blue (RGB) are primary colours. Gamma expansion is used to get their linear intensity encoding to convert image into approximate level of grey

Greyscale

Speed Up Robust Features (SURF) Computer vision algorithm used for object recognition SURF is used to create an image pyramid It filters the pyramids appropriately to detect points of interest. By calculating the features it then compare with features of another image to find matches.

Speed Up Robust Features (SURF) Algorithm

Feature detection

Feature comparison

OpenGL Cross-platform API for writing applications that produce 2D and 3D computer graphics. Is able to draw complex three-dimensional objects in real-time Is capable of interfacing with other libraries. Hide complexities of interfacing with different 3D accelerators

User Interface Specification

Object Orientated Design

Object Orientated Design in detail

Term 3 Tweak algorithm stability. OpenGL virtual camera Calibration Superimpose 3D object on marker. Verify requirements. Term 4 Testing and evaluating software Create User and Technical Manual. Project Plan

_reality_marker_tags References: