Despite the ease with which humans recognize everyday objects, the processes by which this occurs have become a central concern in cognitive science, because object recognition is actually very difficult; for example, computer scientists have only been partially successful in creating computer programs for recognizing objects, and even those programs stretch the computational limits of the most sophisticated machines. Since humans are "good at" object recognition, this research will focus on human abilities, with emphasis on how computational complexities might be handled. Human recognition takes place over a time span of about 100 ms., and the research will use newly developed techniques to control exactly what information is available during that period of time. The working hypothesis underlying this research is that for humans computational burdens are reduced because the brain uses certain types of information early in that time period and other types of information later in that time period. For example, early in time general information about the shape or orientation of an object might be used to narrow down the possibilities, whereas later in time information about more idiosyncratic details would be used to arrive at the proper identification. The research will examine a number of possible types of information that have been suggested in the psychological and computer science literatures. The research will also use several related techniques, because each has its own strengths and weaknesses. Initial work will use relatively simple objects for exploration; later work will use large samples of common objects. Later work will also seek to extend principles of earlier work to the perception of objects within scenes, and to the process of word perception. The knowledge gained will help in the design of robots for a variety of purposes and of aids for visually disabled persons.
