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Conference Paper

Image-based 4-d Reconstruction Using 3-d Change Detection

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Ulusoy,  Osman
Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Citation

Ulusoy, O., & Mundy, J. L. (2014). Image-based 4-d Reconstruction Using 3-d Change Detection. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision - ECCV 2014. 13th European Conference. Proceedings, Part 3 (pp. 31-45). Cham et al.: Springer International Publishing. doi:10.1007/978-3-319-10578-9_3.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0024-E2E7-8
Abstract
This paper describes an approach to reconstruct the complete history of a 3-d scene over time from imagery. The proposed approach avoids rebuilding 3-d models of the scene at each time instant. Instead, the approach employs an initial 3-d model which is continuously updated with changes in the environment to form a full 4-d representation. This updating scheme is enabled by a novel algorithm that infers 3-d changes with respect to the model at one time step from images taken at a subsequent time step. This algorithm can effectively detect changes even when the illumination conditions between image collections are significantly different. The performance of the proposed framework is demonstrated on four challenging datasets in terms of 4-d modeling accuracy as well as quantitative evaluation of 3-d change detection.