We present an approach for object instance detection that uses model recommendation to predict a subset of relevant exemplar models for object detection based on an testing image at runtime. An initial subset of randomly selected exemplar models, the probe set, is first applied to the testing image, and its responses are used, in conjunction with a rating matrix, to predict the responses of all...

Considerable research has addressed whether the cognitive and neural representations recruited by faces are similar to those engaged by other types of visual stimuli. For example, research has examined the extent to which objects of expertise recruit holistic representation and engage the fusiform face area. Little is known, however, about the domain-specificity of the exemplar pooling processe...

Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule...

Nosofsky (1986) proposed and tested a unified quantitative approach to modeling performance in tasks of multidimensional stimulus identification and categorization. The approach was based on the assumption that both identification and categorization decisions are governed by similarity comparisons with individually stored exemplars. By modeling patterns of identification confusions, a multidime...

Most studies of multiple-cue judgment focus on learning by individuals. In a multiple-cue judgment task we examined if people acquire rule or exemplar knowledge as a function of learning the task alone or in dyads. The expectation was that learning in dyads should promote explicit rule-based thinking as a consequence of increased verbalization (a social abstraction effect) and produce a larger ...

Recent ideas about category learning have favored exemplar processes over prototype processes. However, research has focused on small, poorly differentiated categories and on task-final performances—both may highlight exemplar strategies. Thus, we evaluated participants' categorization strategies and standard categorization models at successive stages in the learning of smaller, less differenti...

Estimating the precise pose of a 3D model in an image is challenging; explicitly identifying correspondences is difficult, particularly at smaller scales and in the presence of occlusion. Exemplar classifiers have demonstrated the potential of detection-based approaches to problems where precision is required. In particular, correlation filters explicitly suppress classifier response caused by ...