In this paper, we present a client-server system for 3D scene change detection. A 3D scene point cloud which stored on the server is reconstructed by (structure-from-motion) SfM technique in advance. On the other hand, the client system in tablets captures query images and sent them to the server to estimate the change area. In order to find region of change, an existing change detection method has been applied into our system. Then the server sends detection result image back to mobile device and visualize it. The result of system test shows that the system could detect change cor- rectly.

[1] N. Snavely, S. M. Seitz and R. Szeliski, “Modeling the World from Internet Photo Collections,” International Journal of Computer Vision, Vol. 80, No. 2, 2008, pp. 189-210. doi:10.1007/s11263-007-0107-3

[2] Y. Ueno, B. Lin, K. Sakai, T. Tamaki, B. Raytchev and K. Kaneda, “Camera Position Estimation for Detecting 3D Scene Change,” 18th Korea-Japan Joint Workshop on Frontiers of Computer Vision, 2012.

[3] J. G. M. Goncaluves, “3D Laser-Based Scene Change Detection for Basic Technical Characteristics/Design Information Verification,” ESARDA Bulletin, No. 45, 2010, pp. 66-72.

[4] T. Pollard and J. Mundy, “Change Detection in a 3D World,” Computer Vision and Pattern Recognition, 2007.

[5] A. Taneja, L. Ballon and M. Pollefeys, “Image Based Detection of Geometric Changes in Urban Environments,” International Conference on Computer Vision, 2001.

[6] B. Lin, Y. Ueno, K. Sakai, T. Tamaki, B. Raytchve, K. Kaneda and K. Ichii, “Image Based Detection of 3D Scene Change,” IEEJ Transactions on Electronics, Information and Systems, Vol. 133, No. 1, 2013, pp. 103-110. doi:10.1541/ieejeiss.133.103

[7] Y. Furukawa and J. Ponce, “Accurate, Dense and Robust Multi-View Stereopsis,” Computer Vision and Pattern Recognition, 2007.

[8] Y. Furukawa and J. Ponce, “Accurate, Dense and Robust Multi-View Stereopsis,” Pattern Analysis and Machine, Vol. 32, No. 8, 2010, pp. 1362-1376. doi:10.1109/TPAMI.2009.161

[9] J. Ryle and N. Hillier, “Alignment and 3D Scene Change Detection for Segmentation in Autonomous Earth Moving,” International Conference on Robotics and Automation, 2011.

[10] B. Neuman, B.Sofman, A. Stentz and J. A. Bagnell, “Segmentation-based online Change Detection for Mobile Robots,” International Conference on Robotics and Automation, 2011.

[11] B. Micusik, “Trajectory Reconstruction from Non-Overlapping Surveillance Cameras with Relative Depth ordering Constraints,” ICCV, 2011.

[12] Y. Kameda, T. Takemasa and Y. Ohta, “Outdoor See-Through Vision Utilizing Surveillance Cameras,” International Conference on Computer Vision, 2004.

[13] J. Melo, A. Naftel, A. Bernardino and J. Santos-Victor, “Viewpoint Independent Detection of Vehicle Trajectories and Lane Geometry form Uncalibrated Traffic Surveillance Cameras,” International Conference on Image Analysis and Recognition, 2004