Are categories learned by forming abstract prototypes or by remembering specific exemplars? Mack, Preston, and Love observed that patterns of functional MRI (fMRI) brain activity were more consistent with patterns of representations predicted by exemplar models than by prototype models. Their work represents the theoretical power of emerging approaches to model-based cognitive neuroscience.

Two commonly used approaches to fill the gaps after objects are removed from digital graphics are: image inpainting and texture synthesis. Both approaches have its advantages and disadvantages. Image inpainting will cause blur, while texture synthesis will lead to loss of linear structures. Criminisi, etc., combined the two approaches to a new algorithm that utilized the advantages of both appr...

Human action can be recognised from a single still image by modelling human-object interactions (HOI), which infers the mutual spatial structure information between human and the manipulated object as well as their appearance. Existing approaches rely heavily on accurate detection of human and object and estimation of human pose; they are thus sensitive to large variations of human poses, occlu...

Recovering lost part of an image plays a great role in image processing. Inpainting is a technique that helps in recovering lost pixels from an image. From the existing techniques of Inpainting, Exemplar Inpainting is one of the fast and better techniques that help in restoring the lost part of an image. Exemplar based method chooses a patch similar to the lost patch from the known area to fill...

Exemplar-based methods have proven their efficiency for the reconstruction of missing parts in a digital image. Texture as well as local geometry are often very well restored by these methods. Some applications, however, require the ability to reconstruct non local geometric features, e.g. long edges. We propose in this paper to endow a particular instance of exemplar-based method with a geomet...

Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this researc...

A novel exemplar-based image inpainting algorithm using the Non-Local Means (NLM) algorithm and Criminisi algorithm is proposed. In order to decrease the error in match rate, the new algorithm adopts the sum of squared differences (SSD) search method for several exemplars to generate a candidate exemplar set. Then it determines the Hausdorff distance as measurement criterion to find a match blo...

The early phases of syntactic acquisition are characterized by many input frequency and item effects, which argue against theories assuming innate access to classical syntactic categories. In formulating an alternative view, we consider both prototype and exemplar-learning models of categorization. We argue for a ‘hybrid’ usage-based view in which acquisition depends on exemplar learning and re...

This paper presents a robust algorithm for exemplar-based image inpainting. We focus on the development of a generic priority function to provide robust performance. With user intervention, the algorithm is easy to be applied to any image contents with different characteristics. We conduct experiments on several kinds of still images and demonstrate the effectiveness of the proposed algorithm. ...