1 October 1990 Three-dimensional line interpretation via local processing
Author Affiliations +
The interpretation of line drawings is known to be very difficult, and has a long history in vision research. However for certain restricted but important types of drawings we have been able to produce good 3-D interpretations quite efficiently using only local image-plane computations. The types of drawings we can handle are line drawings of 3-D space curves, for instance, a drawing of the 3-D path followed by a butterfly or a line drawing of a potato chip. Such line drawings are, of course, intrinsically ambiguous - there is simply not enough information in the 2-D image to arrive at a unique 3-D interpretation. Despite this difficulty, there remains the fact that for any given image all people see pretty much exactly the same 3-D interpretation (or sometimes a small number of interpretations). People, therefore, must be bringing additional knowledge or assumptions to the problem. In this paper we show that by picking the smoothest 3-D space curve that is consistent with the image data we can obtain a 3-D interpretation which is very similar to the people's interpretation. The teleological motivation for selecting the smoothest 3-D space curve is that it is the most stable 3-D interpretation, and thus in one sense the most likely 3-D interpretation. The process of computing the smoothest 3-D space curve is carried out by simple, local processing that can be implemented by a neural network.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexander P. Pentland, Alexander P. Pentland, Jeff Kuo, Jeff Kuo, } "Three-dimensional line interpretation via local processing", Proc. SPIE 1249, Human Vision and Electronic Imaging: Models, Methods, and Applications, (1 October 1990); doi: 10.1117/12.19685; https://doi.org/10.1117/12.19685


A new double views motion deblurring method
Proceedings of SPIE (December 14 2015)
3D primitive reconstruction using the line segment
Proceedings of SPIE (March 25 2003)
Object model construction by invariance and photogrammetry
Proceedings of SPIE (August 05 1997)

Back to Top