Neural network approach to object recognition and image partitioning within a resolution hierarchy
Joachim Utans, Gene R. Gindi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Object recognition is a complex task involving simultaneous problems in grouping, segmentation, and matching. Previous work involved an objective function formulation of the problem, resulting in a uniform method of addressing problems in object recognition that have heretofore been approached by heterogenous complex vision systems. The complexity of our objective functions resulted in numerous optimization failures, not unexpectedly. Here we propose to prime the system with estimates of the objects parameters at a coarse, more abstract, scale. We discuss how this might be done. These initial values are expected to bring the state of the system closer to good minima.