  Augmented reality (AR) using camera images in mobile devices is becoming
popular for tourism promotion. However, obstructions such as tourists appearing
in the camera images may cause the camera pose estimation error, resulting in
CG misalignment and reduced visibility of the contents. To avoid this problem,
Indirect AR (IAR), which does not use real-time camera images, has been
proposed. In this method, an omnidirectional image is captured and virtual
objects are synthesized on the image in advance. Users can experience AR by
viewing a scene extracted from the synthesized omnidirectional image according
to the device's sensor. This enables robustness and high visibility. However,
if the weather conditions and season in the pre-captured 360 images differs
from the current weather conditions and season when AR is experienced, the
realism of the AR experience is reduced. To overcome the problem, we propose a
method for correcting the intensity and texture of a past omnidirectional image
using camera images from mobile devices. We first perform semantic
segmentation. We then reproduce the current sky pattern by panoramic image
composition and inpainting. For the other areas, we correct the intensity by
histogram matching. In experiments, we show the effectiveness of the proposed
method using various scenes.
