THESIS
2019
ix, 33 pages : illustrations ; 30 cm
Abstract
Real-time surface mapping and tracking is the core technology behind augmented reality
applications. The growing trend of integrating depth sensors into mobile devices
provides a great opportunity for enhancing the experience of interaction with reality. This
work presents a system that utilizes the RGB-D cameras of mobile devices, for tracking
and reconstructing dense surface in real-time. This task is challenging because the low
computing power and memory capacity on consumer mobile platform limit the scale and
precision of the reconstruction. To scale up scene size and provide smooth integration
experience, we implemented memory efficient data representation and caching methods,
and also make the integration and visualization processes highly parallel. This thesis illustrates...[
Read more ]
Real-time surface mapping and tracking is the core technology behind augmented reality
applications. The growing trend of integrating depth sensors into mobile devices
provides a great opportunity for enhancing the experience of interaction with reality. This
work presents a system that utilizes the RGB-D cameras of mobile devices, for tracking
and reconstructing dense surface in real-time. This task is challenging because the low
computing power and memory capacity on consumer mobile platform limit the scale and
precision of the reconstruction. To scale up scene size and provide smooth integration
experience, we implemented memory efficient data representation and caching methods,
and also make the integration and visualization processes highly parallel. This thesis illustrates
the implementation of each pipeline stage, including the underlying data structure,
pre-processing, tracking, integration, rendering and caching. The overall performance
evaluation and its application are also demonstrated with a conclusion.
Post a Comment