c-Space: Time-evolving 3D Models (4D) from Heterogeneous Distributed Video Sources

Abstract

We introduce c-Space, an approach to automated 4D reconstruction of dynamic real world scenes, represented as time-evolving 3D geometry streams, available to everyone. Our novel technique solves the problem of fusing all sources, asynchronously captured from multiple heterogeneous mobile devices around a dynamic scene at a real word location. To this end all captured input is broken down into a massive unordered frame set, sorting the frames along a common time axis, and finally discretizing the ordered frame set into a time-sequence of frame subsets, each subject to photogrammetric 3D reconstruction. The result is a time line of 3D models, each representing a snapshot of the scene evolution in 3D at a specific point in time. Just like a movie is a concatenation of time-discrete frames, representing the evolution of a scene in 2D, the 4D frames reconstructed by c-Space line up to form the captured and dynamically changing 3D geometry of an event over time, thus enabling the user to interact with it in the very same way as with a static 3D model. We do image analysis to automatically maximize the quality of results in the presence of challenging, heterogeneous and asynchronous input sources exhibiting a wide quality spectrum. In addition we show how this technique can be integrated as a 4D reconstruction web service module, available to mobile end-users.