Feature Tracking And Mapping On The Spatiotemporal Surface
H. Harlyn Baker, Robert C. Bolles · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1988
The previous implementations of our Epipolar-Plane Image Analysis depth measuring technique for a moving vehicle [3] demonstrated the feasibility and benefits of the approach, but were carried out for restricted camera geometries. The question of more general geometries made utility for autonomous navigation uncertain. We have developed a generalization of the analysis that a) enables varying view direction (including varying over time), b) provides three-dimensional connectivity information for building coherent spatial descriptions of observed objects, and c) operates sequentially, allowing initiation and refinement of scene feature estimates while the sensor is in motion. To implement this generalization it was necessary to develop an explicit description of the evolution of images over time. We have achieved this by building a process that creates a set of two-dimensional manifolds defined at the zeros of a three-dimensional spatiotemporal Laplacian. These manifolds represent explicitly both the spatial and temporal structure of the temporally-evolving imagery, and we term them spatiotemporal surfaces. Named the Weaving Wall, the process which builds these surfaces operates over images as they arrive from the sensor, knitting together, along a parallel frontier, connected descriptions of images as they evolve over time. We describe the sequential construction of these surfaces and their use in three-dimensional scene reconstruction. The use of the process in other domains will be highlighted by showing its application in the area of medical imaging.