CONFERENCE PROCEEDINGS
Advanced Search >
Home > Proceedings > Volume 11169 > Article
Translator Disclaimer
19 September 2019 Semantic segmentation of panoramic images using a synthetic dataset
Yuanyou Xu; Kaiwei Wang; Kailun Yang; Dongming Sun; Jia Fu
Author Affiliations +
Proceedings Volume 11169, Artificial Intelligence and Machine Learning in Defense Applications; 111690B (2019) https://doi.org/10.1117/12.2532494
Event: SPIE Security + Defence, 2019, Strasbourg, France
Abstract
Panoramic images have advantages in information capacity and scene stability due to their large field of view (FoV). In this paper, we propose a method to synthesize a new dataset of panoramic image. We managed to stitch the images taken from different directions into panoramic images, together with their labeled images, to yield the panoramic semantic segmentation dataset denominated as SYNTHIA-PANO. For the purpose of finding out the effect of using panoramic images as training dataset, we designed and performed a comprehensive set of experiments. Experimental results show that using panoramic images as training data is beneficial to the segmentation result. In addition, it has been shown that by using panoramic images with a 180 degree FoV as training data the model has better performance. Furthermore, the model trained with panoramic images also has a better capacity to resist the image distortion. Our codes and SYNTHIA-PANO dataset are available: https://github.com/Francis515/SYNTHIA-PANO.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Yuanyou Xu, Kaiwei Wang, Kailun Yang, Dongming Sun, and Jia Fu "Semantic segmentation of panoramic images using a synthetic dataset", Proc. SPIE 11169, Artificial Intelligence and Machine Learning in Defense Applications, 111690B (19 September 2019); https://doi.org/10.1117/12.2532494
PROCEEDINGS
 15 PAGES + PRESENTATION
DOWNLOAD PDF SAVE TO MY LIBRARY
WATCH
PRESENTATION
SHARE
GET CITATION
< Previous Article
|
Next Article >
Advertisement
Advertisement
KEYWORDS
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top