Abstract
One of the key problems in the large scale reconstruction of 3D scenes from images is how to efficiently compute image relations in large databases. Finding images depicting the same 3D geometry is the pre-requisite for camera calibration and 3D reconstruction. In this chapter we present a simple and compact descriptor that enables us to efficiently compute similarity between video sequences. In addition to providing a similarity measure, the descriptor also makes it possible to select individual video frames that match together. With our descriptors, this computation can be done in a time similar to that required by the traditional SIFT algorithm to match just two images. Using the presented descriptors, we can build a large relation graph between video streams or image sequences. This relation graph is used later in assembling a large geometric model.
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Parys, R., Liefers, F., Schilling, A. (2013). Compact Descriptor for Video Sequence Matching in the Context of Large Scale 3D Reconstruction. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) Multimedia and Internet Systems: Theory and Practice. Advances in Intelligent Systems and Computing, vol 183. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32335-5_6
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DOI: https://doi.org/10.1007/978-3-642-32335-5_6
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