Comparing crowding in human and ideal observers.

A visual target is more difficult to recognize when it is surrounded by other, similar objects. This breakdown in object recognition is known as crowding. Despite a long history of experimental work, computational models of crowding are still sparse. Specifically, few studies have examined crowding using an ideal-observer approach. Here, we compare crowding in ideal observers with crowding in humans. We derived an ideal-observer model for target identification under conditions of position and identity uncertainty. Simulations showed that this model reproduces the hallmark of crowding, namely a critical spacing that scales with viewing eccentricity. To examine how well the model fits quantitatively to human data, we performed three experiments. In Experiments 1 and 2, we measured observers' perceptual uncertainty about stimulus positions and identities, respectively, for a target in isolation. In Experiment 3, observers identified a target that was flanked by two distractors. We found that about half of the errors in Experiment 3 could be accounted for by the perceptual uncertainty measured in Experiments 1 and 2. The remainder of the errors could be accounted for by assuming that uncertainty (i.e., the width of internal noise distribution) about stimulus positions and identities depends on flanker proximity. Our results provide a mathematical restatement of the crowding problem and support the hypothesis that crowding behavior is a sign of optimality rather than a perceptual defect.

Measuring design investment in firms: Conceptual foundations and exploratory UK survey

The importance of design to company and national performance has been widely discussed, with a number of studies investigating the value or impact of design on performance. However, none of these studies has measured design investment as an input against which performance can be compared. As yet, there is no established way in which design investment might be measured. Without such a method, we cannot develop a reliable picture, akin to that for R&D spending, on the impact of design spending on company performance. This paper presents a conceptual framework for the measurement of design investment and applies this framework in a survey of UK firms. The framework describes design as being part of the creation and commercialization of new products and services. The survey highlights some surprising patterns of design spend in the reported sample and demonstrates the viability of the underpinning framework. A revised framework is proposed that situates design investment in the context of R&D. The model has implications for policy makers trying to understand the role and scale of design in the private sector, for managers wishing to optimize their design investments and for academics seeking to measure the value of design. © 2013 Published by Elsevier B.V.