Recently, augmented reality has become very popular and has appeared in our daily life with gaming, guiding
systems or mobile phone applications. However, inserting object in such a way their appearance seems natural is still an
issue, especially in an unknown environment. This paper presents a framework that demonstrates the capabilities of
Kinect for convincing augmented reality in an unknown environment. Rather than pre-computing a reconstruction of the
scene like proposed by most of the previous method, we propose a dynamic capture of the scene that allows adapting to
live changes of the environment. Our approach, based on the update of an environment map, can also detect the position
of the light sources. Combining information from the environment map, the light sources and the camera tracking, we
can display virtual objects using stereoscopic devices with global illumination effects such as diffuse and mirror
reflections, refractions and shadows in real time.
An efficient system that upsamples depth map captured by Microsoft Kinect while jointly reducing the effect of noise is
presented. The upsampling is carried by detecting and exploiting the piecewise locally planar structures of the downsampled
depth map, based on corresponding high-resolution RGB image. The amount of noise is reduced by accumulating
the downsampled data simultaneously. By benefiting from massively parallel computing capability of modern commodity
GPUs, the system is able to maintain high frame rate. Our system is observed to produce the upsampled depth map that is
very close to the original depth map both visually and mathematically.
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