Object recognition and categorization research are both concerned with understanding how input information matches object information in memory. It is therefore surprising that these two fields have evolved independently, without much cross-fertilization. It is the main objective of this paper to lay out the basis of a dialogue between object recognition and categorization research, with the hope of raising issues that could cross-fertilize both domains. To this end, the paper develops diagnostic recognition, a framework which formulates recognition performance as an interaction of task constraints and object information. I argue and present examples suggesting that diagnostic recognition could be fruitfully applied to the understanding of everyday object recognition. Issues are raised regarding the psychological status of the interactions specified in the framework.