Feedforward and Feedback Processing of Spatiotemporal Tubes for Efficient Object Localization

Abstract

We introduce a new set of mechanisms for tracking entities through videos, at substantially less expense than required by standard methods. The approach combines inexpensive initial processing of individual frames together with integration of information across long time spans (multiple frames), resulting in the recognition and tracking of spatially and temporally contiguous entities, rather than focusing on the individual pixels that comprise those entities.