Paper Info
Title
360 Stitching from Dual-Fisheye Cameras Based on Feature Cluster Matching
Abstract
In the past years, captures made by dual-fisheye lens cameras have been used for virtual reality, 360 broadcasting and many other applications. For these scenarios, to provide a good- quality experience, the alignment of the boundaries between the two images to be stitched must be done properly. However, due to the peculiar design of dual-fisheye cameras and the high variance between different captured scenes, the stitching process can be very challenging. In this work, we present a 360 stitching solution based on feature cluster matching. It is an adaptive stitching technique based on the extraction of feature cluster templates from the stitching region. It is proposed an alignment based on the template matching of these clusters, successfully reducing the discontinuities in the full-view panorama. We evaluate our method on a dataset built from captures made with an existing camera of this kind, the Samsung's Gear 360. It is also described how we can extend these concepts from image stitching to video stitching using the temporal information of the media. Finally, we show that our matching method outperforms a state-of-the-art matching technique for image and video stitching.
Year
DOI
Venue
2018
10.1109/SIBGRAPI.2018.00047
2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
Keywords
Field
DocType
dual fisheye,virtual reality,panorama image,stitching,360 camera
Template matching,Computer vision,Broadcasting,Image stitching,Virtual reality,Panorama,Computer science,Feature extraction,Lens (optics),Artificial intelligence,Template
Conference
ISSN
ISBN
Citations 
1530-1834
978-1-5386-9265-3
0
PageRank 
References 
Authors
0.34
7
8
Name
Order
Citations
PageRank
Tancredo Souza100.34
Rafael Alves Roberto2247.26
João Paulo S. M. Lima3158.81
Veronica Teichrieb418442.78
Jonysberg P. Quintino506.76
Fabio Q. B. da Silva651553.57
André L. M. Santos722920.15
Helder Pinho802.37