In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection al...
We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features...
: In feature modelling, constraints can be used to store design intent in a model. Interaction constraints are an important type of constraints, which limit the extent to which fea...