Authors:
Rafael Roberto
1
;
Daniel Perazzo
1
;
João Paulo Lima
2
;
1
;
Veronica Teichrieb
1
;
Jonysberg Peixoto Quintino
3
;
Fabio Q. B. da Silva
4
;
Andre L. M. Santos
4
and
Helder Pinho
5
Affiliations:
1
Voxar Labs, Centro de Informática, Universidade Federal de Pernambuco, Recife/PE, Brazil
;
2
Departamento de Computação, Universidade Federal Rural de Pernambuco, Recife/PE, Brazil
;
3
Projeto de P&D CIn/Samsung, Universidade Federal de Pernambuco, Recife/PE, Brazil
;
4
Centro de Informática, Universidade Federal de Pernambuco, Recife/PE, Brazil
;
5
SiDi, Campinas/SP, Brazil
Keyword(s):
Stitching 360, Dual-fish Eye Camera, Panoramic Image.
Abstract:
Full panoramic images have several applications, ranging from virtual reality to 360º broadcasting. Such
visualization method is growing, especially after the popularization of dual-fisheye cameras, which are
compact and easy-to-use 360º
imaging devices, and low-cost platforms that allow immersive experiences.
However, low-quality registration and compositing in which artifacts are noticeable in the stitching area can
harm the user experience. Although it is challenging to compose such images due to their narrow overlap area,
recent works can provide good results when performing a global alignment. Nevertheless, they often cause
artifacts since global alignment is not able to address every aspect of an image. In this work, we present a
stitching method that performs local refinements to improve the registration and compositing quality of 360º
images and videos. It builds on a feature clustering approach for global alignment. The proposed technique
applies seam estimation an
d rigid moving least squares to remove undesired artifacts locally. Finally, we
evaluate both to select the best result between them using a seam evaluation metric. Experiments showed that
our method reduced the stitching error in at least 42.56% for images and 49.45% for videos when compared
with existing techniques. Moreover, it provided the best results in all tested images and in 94.52% of the video
frames.
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