Is one object enough? Diagnosticity of single objects for fast scene categorization

We can categorize our environment into different scene categories (e.g., a kitchen or a highway) within a glance. Object information has been suggested to play a crucial role in this process, and some proposals even claim that recognition of a single object can be sufficient to categorize the scene around it. Here, we tested this claim by having participants categorize real-world scene photographs reduced to a single, cut-out object. We show that single objects can indeed be sufficient for correct scene categorization and that scene category information can be extracted within 50 ms of object presentation. Furthermore, we identify the exact properties that make certain objects diagnostic of scene categories using human ratings and statistical measures derived from labelled image databases. Interestingly, fast scene categorization is best explained by human ratings of estimated frequency and specificity of the presented objects for the target scene category and less so by objective database measures. Taken together, our findings support a central role of object information during fast scene categorization, showing that single objects can be indicative of a scene category if they are assumed to frequently and exclusively occur in a certain environment.