Monday, January 18, 2010

Understanding versus Interpretation -- a philosophical distinction

Today I want to bring up an interesting discussion regarding the connotation of the word "understanding" versus "interpretation," particularly in the context of "scene understanding" versus "scene interpretation." While many vision researchers use these terms interchangeably, I think it is worthwhile to make the distinction, albeit a philosophical one.

On Understanding
While everybody knows that the goal of computer vision is to recognize all of the objects in an image, there is plenty of disagreement about how to represent objects and recognize them in the image. There is a physicalist account (from Wikipedia: Physicalism is a philosophical position holding that everything which exists is no more extensive than its physical properties), where the goal of vision is to reconstruct veridical properties of the world. This view is consistent with the realist stance in philosophy (think back to Philosophy 101) -- there exists a single observer-independent 'ground-truth' regarding the identities of all of the objects contained in the world. The notion of vision as measurement is very strong under this physicalist account. The stuff of the world is out there just waiting to be grasped! I think the term "understanding" fits very well into this truth-driven account of computer vision.

On interpretation
The second view, a postmodern and anti-realist one, is of vision as a way of interpreting scenes. The shift is from veridical recovery of the properties of the world from an image (measurement) to the observer-dependent interpretation of the input stimulus. Under this account, there is no need to believe in a god's eye 'objective' view of the world. Image interpretation is the registration of an input image with a vast network of past experience, both visual and abstract. The same person can vary their own interpretation of an input as time passes and the internal knowledge based has evolved. Under this view, two distinct robots could provide very useful yet distinct 'image interpretations' of the same input image. The main idea is that different robots could have different interpretation-spaces, that is they could obtain incommensurable (yet very useful!) interpretations of the same image.

It has been argued by Donald Hoffman (Interface Theory of Perception) that there is no reason why we should expect evolution to have driven humans towards veridical perception. In fact, Hoffman argues that natures drives veridical perception towards extinction and it only makes sense to speak of perception as guiding agents towards pragmatic interpretations of their environment.

In philosophy of science, there is the debate of whether the field of physics is unraveling some ultimate truth about the world versus physics painting a coherent and pragmatic picture of the world. I've always viewed science as an art and I embrace my anti-realist stance -- which has been shaped by Thomas Kuhn, William James, and many others. While my scientific interests have currently congealed in computer vision, it is no surprise that I'm finding conceptual agreement between my philosophy of science and my concrete research efforts in object recognition.