Change Detection from a Street Image Pair using CNN Features and Superpixel Segmentation

Ken Sakurada and Takayuki Okatani

Abstract

This paper proposes a method for detecting changes of a scene using a pair of its vehicular, omnidirectional images. Previous approaches to the problem require the use of a 3D scene model and/or pixel-level registration between different time images. They are also computationally costly for estimating city-scale changes. We propose a novel change detection method that uses features of convolutional neural network (CNN) in combination with superpixel segmentation. Comparison of CNN features gives a low-resolution map of scene changes that is robust to illumination changes and viewpoint differences. Superpixel segmentation of the scene images is integrated with this low-resolution map to estimate precise segmentation boundaries of the changes. Our motivation is to develop a method for detecting city-scale changes, which can be used for visualization of damages of a natural disaster and subsequent recovery processes as well as for the purpose of maintaining/updating the 3D model of a city. We have created a dataset named Panoramic Change Detection Dataset, which will be made publicly available for evaluating the performances of change detection methods in these scenarios. The experimental results using the dataset show the effectiveness of our approach.

Session

Poster 1

Files

PDF iconExtended Abstract (PDF, 408K)
PDF iconPaper (PDF, 4M)
ZIP iconSupplemental Materials (ZIP, 18M)

DOI

10.5244/C.29.61
https://dx.doi.org/10.5244/C.29.61

Citation

Ken Sakurada and Takayuki Okatani. Change Detection from a Street Image Pair using CNN Features and Superpixel Segmentation. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 61.1-61.12. BMVA Press, September 2015.

Bibtex

@inproceedings{BMVC2015_61,
	title={Change Detection from a Street Image Pair using CNN Features and Superpixel Segmentation},
	author={Ken Sakurada and Takayuki Okatani},
	year={2015},
	month={September},
	pages={61.1-61.12},
	articleno={61},
	numpages={12},
	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
	publisher={BMVA Press},
	editor={Xianghua Xie, Mark W. Jones, and Gary K. L. Tam},
	doi={10.5244/C.29.61},
	isbn={1-901725-53-7},
	url={https://dx.doi.org/10.5244/C.29.61}
}