Acquiring 3D indoor environments with variability and repetition

Y.M. Kim, N.J. Mitra, D.M. Yan, L. Guibas
Siggraph Asia, volume 31, issue 6, article no. 138, (2012)

Acquiring 3D indoor environments with variability and repetition


Acquisition, Scene understanding, Shape analysis, Real-time modeling


​office scene input single-view scan recognized objects scan + overlaid objects Figure 1: (Left) Starting from a single view scan of a 3D environment obtained using a fast range scanner, we perform scene understanding by recognizing repeated objects, while factoring out their modes of variability (middle, right). The repeating objects have been learned beforehand as low complexity models, along with their variability modes. We extract these objects despite a poor quality input scan with large missing parts and many outliers. For reference, we also show a scene photograph, which is not available to the algorithm. Large-scale acquisition of exterior urban environments is by now a well-established technology, supporting many applications in search, navigation, and commerce. The same is not true for indoor environments, however: access is often restricted and the spaces may be cluttered. In addition, such environments typically contain a high density of repeated objects (e.g., tables, chairs, monitors, etc.) in regular or non-regular arrangements with significant pose variations and articulations. In this paper, we exploit the special structure of indoor environments to accelerate their 3D acquisition and recognition with a low-end handheld scanner. Our approach runs in two phases: (i) a learning phase, where we acquire 3D models of frequently occurring objects and capture their variability modes from only a few scans, and (ii) a recognition phase, where from a single scan of new areas, we identify previously seen objects, but in varying poses and locations. This greatly accelerates the capture process (average recognition time of 200ms/model). We demonstrate our framework with the acquisition of typical areas of a university building including cubicle or desk areas, auditoriums, etc.


DOI: 10.1145/2366145.2366157


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