In pattern recognition field, objects are usually represented by multiple features (multimodal
features). For example, to characterize a natural scene image, it is essential to extract a set …

In recent years we witnessed a surge of interest in subspace learning for image
classification. However, the previous methods lack of high accuracy since they do not …

Learning discriminative subspaces for multimodality image analysis has been an
extensively discussed topic over the past several decades in interdisciplinary fields. It has …

An efficient classification system uses only the most representative features extracted from
images in order to reach a decision. A multimodal system may consider multiple sources of …

One primary focus in multimodal feature extraction is to find the representations of individual
modalities that are maximally correlated. As a well-known measure of dependence, the …

Multimodal data is more and more popular in recent years. It is most interesting and
challenging to learn multimodal data representation which affects the performance of …

As a key dimensionality reduction technique in pattern recognition, feature selection has
been widely used in information retrieval, text classification and genetic data analysis. In …

This paper introduces a novel approach for search and retrieval of multimedia content. The
proposed framework retrieves multiple media types simultaneously, namely 3D objects, 2D …

Multimodal recognition has recently become more attractive and common method in
multimedia information retrieval. In many cases it shows better recognition results than using …

In computer vision and multimedia analysis, it is common to use multiple features (or
multimodal features) to represent an object. For example, to well characterize a natural …