  Flying Triangulation sensors enable a free-hand and motion-robust 3D data
acquisition of complex shaped objects. The measurement principle is based on a
multi-line light-sectioning approach and uses sophisticated algorithms for
real-time registration (S. Ettl et al., Appl. Opt. 51 (2012) 281-289). As
"single-shot principle", light sectioning enables the option to get surface
data from one single camera exposure. But there is a drawback: A pixel-dense
measurement is not possible because of fundamental information-theoretical
reasons. By "pixel-dense" we understand that each pixel displays individually
measured distance information, neither interpolated from its neighbour pixels
nor using lateral context information. Hence, for monomodal single-shot
principles, the 3D data generated from one 2D raw image display a significantly
lower space-bandwidth than the camera permits. This is the price one must pay
for motion robustness. Currently, our sensors project about 10 lines (each with
1000 pixels), reaching an considerable lower data efficiency than theoretically
possible for a single-shot sensor. Our aim is to push Flying Triangulation to
its information-theoretical limits. Therefore, the line density as well as the
measurement depth needs to be significantly increased. This causes serious
indexing ambiguities. On the road to a single-shot 3D movie camera, we are
working on solutions to overcome the problem of false line indexing by
utilizing yet unexploited information. We will present several approaches and
will discuss profound information-theoretical questions about the information
efficiency of 3D sensors.
