On the Future of Object Recognition: The Contribution of Color

Abstract

Cognitive theories of object recognition have traditionally emphasized structural components (Biederman, 1987; Grossberg & Mingolla, 1985). The idea that object recognition is largely driven by shape was advantageous to theory building because of its economy (i.e., only a single dimension needed to be attended and there are a finite number of mutually exclusive components). However, recent work provides evidence that surface level information (e.g., object color) is readily used in object recognition (Rossion & Pourtois, 2004; Tanaka & Presnell, 1999; Therriault et al., 2009; & Naor-Raz et al., 2003). The purpose of this chapter is two-fold: to present results from experiments that more closely examine color’s influence on object recognition and to reconcile these results with traditional theories of object recognition. Section 2 contains a historical overview of the claims made between strucutral (i.e., edge) and view-point dependent (i.e., surface + edge) characterizations of object recognition. Although the debate may be subsiding over the status of viewpoint invariance, many open questions remain concerning how color contributes to the processing and recognition of objects. Section 3 reviews conflicting research on the role of color in object recognition. Some studies fail to find any effects of color upon recognition, others find evidence for only high color diagnostic objects, and still others find that color readily influences recognition. This section concludes by offering some explanations for differences in obtained results. Section 4 presents a recent set of experiments from my lab exploring the role of color in recognition, conceptualization, and language use. Most striking, the results from four different experiments are identical with respect to color. The presentation of correctly colored items always enhanced recognition and conceptualization of the objects. In Section 5, the early conceptual analogy used in object recognition (i.e., speech segmentation) is reviewed and updated. I propose that object recognition is more anlagous to word recognition in reading. This is a more apt analogy because it can accomodate both structural and view-point evidence. Finally, Section 6 argues that evidence calls for a more nuanced, flexible and integrated theory of object recognition, one that includes both bottom-up and top-down processing. The chapter concludes that the study of color vision is a fruitful area from which to gain a deeper understanding of object recognition generally; and that this pursuit would benefit greatly from the contribution of disciplines beyond cognition (e.g., neuroscience, biology, and linguistics).