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Knowing An Object Is There Does Not Necessarily Mean You Know What It Is
How do we recognize objects in our complex world? According to one prevailing view, when our visual system parses a visual scene into individual objects, it simultaneously classifies those objects in familiar categories such as "dog", "car", or "chair". In other words, as soon as you know an object is there, you know what it is. New work by NSF-funded investigators from the Temporal Dynamics Learning Center overturns this view. One challenge for the scientific study of object recognition is that it happens so rapidly; we can recognize objects in less than 1/10 of a second. Michael Mack, Isabel Gauthier, Javid Sadr, and Thomas Palmeri used a variety of experimental techniques to examine in detail how object recognition unfolds over time, from as little as 1/100 of a second of exposure. Under some circumstances the time-course of detecting an object and categorizing an object are the same, but when the objects were upside-down or blurred, people could now detect the presence of objects before they could categorize them. Detecting an object and recognizing an object as a member of a category are separate decisions that rely on different visual information. This basic result has general implications for understanding the mechanisms of object recognition and how they might change over learning. Future work could investigate the time-course of categorization experts in different domains (e.g., radiologists and baggage screeners) and suggest the best way to present information for different types of decisions.