This paper is about shape fitting to regions that segment an image and some applications that rely on the abstraction that offers. The novelty lies in three areas: (1) we fit a shape drawn from a selection of shape families, not just one class of shape, using a supervised classifier; (2) We use results from the classifier to match photographs and artwork of particular objects using a few qualit...

Through online games, people can collectively solve large-scale computational problems. E ach year, people around the world spend billions of hours playing computer games. What if all this time and energy could be channeled into useful work? What if people playing computer games could, without consciously doing so, simultaneously solve large-scale problems? Despite colossal advances over the pa...

Abstract The desire for positive self-view may lead people, sometimes, to self-deception. Previous studies demonstrated that such deception takes the form of selective memory search, rationalizing opposing arguments and distorted self-signaling. This study identifies a new mechanism – “accidentally” eliminating the interpretation that poses a threat to the positive self-view. Specifically, we s...

We define an approach to benchmarking, Purpose-Based Benchmarks, which explicitly and comprehensively measures the ability of a computing system to reach a goal of human interest. This contrasts with the traditional approach of defining a benchmark as a task to be timed, or as the rate at which some activity is performed. Purpose-Based Benchmarks are more difficult to create than traditional be...

Recent research trends of the last five years show that richly annotated corpora inspire novel research. These richly annotated corpora are indispensable for progressing research, but also more difficult to manage and maintain due to increasing complexity – what is needed is a way to manage the annotation project in its entirety. However, annotation project management has received little attent...

We show that transductive (cross-domain) learning is an important consideration in building a general-purpose language identification system, and develop a feature selection method that generalizes across domains. Our results demonstrate that our method provides improvements in transductive transfer learning for language identification. We provide an implementation of the method and show that o...