Detecting Structural Scene Changes

Abstract

This paper proposes a method for detecting temporal changes of the three-dimensional structure of an outdoor scene from its multi-view images captured at two separate times. For the images, we consider those captured by a camera mounted on a vehicle running in a city street. The method estimates scene structures probabilistically, not deterministically, and based on their estimates, it evaluates the probability of structural changes in the scene, where the inputs are the similarity of the local image patches among the multi-view images. The aim of the probabilistic treatment is to maximize the accuracy of change detection, behind which there is our conjecture that although it is dicult to estimate the scene structures deterministically, it should be easier to detect their changes. The proposed method is compared with the methods that use multi-view stereo (MVS) to reconstruct the scene structures of the two time points and then differentiate them to detect changes. The experimental results show that the proposed method outperforms such MVS-based methods.

Paper

Ken Sakurada, Takayuki Okatani, and Koichiro Deguchi, Detecting Changes in 3D Structure of a Scene from Multi-view Images Captured by a Vehicle-mounted Camera, CVPR2013

@inproceedings{sakurada2013detecting,
  title={Detecting changes in 3D structure of a scene from multi-view images captured by a vehicle-mounted camera},
  author={Sakurada, Ken and Okatani, Takayuki and Deguchi, Koichiro},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={137--144},
  year={2013}
}

Results

Video

Dataset

Click here to go to “Change Detection Dataset” page.

Acknowledgments

This work was supported by Grant-in-Aid for Scientific Research on Innovative Areas “Shitsukan” (No. 23135501) and JSPS KAKENHI Grant Number 2230057.