Proceedings of the Annual Meeting of the Cognitive Science Society

fficient categorizations of complex stimuli require effective encodings of their distinctive properties. In the object recognition literature, scene categorization is often pictured as the ultimate result of a progressive reconstruction of the input scene from precise local measurements such as boundary edges. However, even complex recognition tasks do not systematically require a complete reconstruction of the input from detailed measurements. It is well established that perception filters the input at multiple spatial scales, each of which could serve as a basis of stimulus encoding. Whe n categorization operates in a space defined with multiple scales, the requirement of finding diagnostic information could change the scale of stimulus encoding. In Schyns and Oliva (1994), we showed that very fast categorizations encoded coarse information before fine information. This paper investigates the influence of categorization on stimulus encodings at different spatial scales. The first experiment tested whether the expectation of finding diagnostic information at a particular scale influenced the selection of this scale for preferred encoding of the input. The second experiment investigated whether the multiple scales of a scene were processed independently, or whether they cooperated (perceptually or categorically) in the recognition of the scene. Results suggest that even though scale perception is mandatory, the scale of stimulus encoding is flexibly adjusted to categorization requirements.