This paper is concerned with the problem of recognizing complex objects rapidly and flexibly. The strategy is based on three main concepts: the use of a generalised local feature detector, an extended learning algorithm, and unique object structure. Most of the paper is devoted to a discussion of the strategy and the architecture that was developed to tackle this problem and the extent of its generality. Implementation and algorithmic considerations are given only briefly as they have already been described in detail elsewhere. A summary of test results is also given.