Physically-based depth of field in augmented reality

In this research work a novel method for rendering and compositing video in augmented reality is presented. The aim of the research is calculating the physically correct result of the depth of field caused by a lens with finite sized aperture. In order to correctly simulate light transport, ray-tracing is used and in a single pass combined with differential rendering to compose the final augmented video.

The image is fully rendered on GPUs, therefore an augmented video can be produced at interactive frame rates in high quality. Proposed method runs on the fly and no video postprocessing is needed.

Automatic image-based 3D head modeling

3D Head Modeling System is software for automatic 3D head model creation from front and profile photograph developed in this work. After loading input images, the facial features are automatically detected. User can manually adjust detected positions to reach better precision. Finally the 3D head model is reconstructed from input images.

3D head reconstruction can be done in three basic steps. In the first two user loads the front and profile head photographs. In the final step the 3D head model is automatically reconstructed. Model can be exported to Collada format for further use in the other applications.

Collada Engine

Collada Engine is package of libraries for loading and rendering digital content saved in collada document files. Libraries support loading geometry, nodes, transformations, textures etc. from .dae files. 3D content is rendered with use of OpenGL. Libraries support also shader loading, compiling and using in rendering. Libraries can be downloaded from this link or from project website.

Libraries are created in Borland Developer Studio and need it for proper function. Basic component needed for 3D model loading is TXMLDocument component from Borland Developer Studio.

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