Since the emergence of extensive multimedia data, feature fusion has been more and more
important for image and video retrieval, indexing and annotation. Existing feature fusion …

Subspace-based methods are known to provide a practical solution for image set-based
object recognition. Based on the insight that local shape differences between objects offer a …

Rotating machinery is ubiquitous, and its failures constitute a major cause of the failures of
transportation infrastructures. Most fault-diagnosis methods for rotating machinery are based …

Beyond linear and kernel-based feature extraction, we propose in this paper the generalized
feature extraction formulation based on the so-called graph embedding framework. Two …

In the field of image set classification, most existing works focus on exploiting effective latent
discriminative features. However, it remains a research gap to efficiently handle this …

In this paper, we propose a novel method that exploits correlation between audio-visual
dynamics of a video to segment and localize objects that are the dominant source of audio …

We propose a novel approach to template based face recognition. Our dual goal is to both
increase recognition accuracy and reduce the computational and storage costs of template …

We propose a deep learning framework for image set classification with application to face
recognition. An Adaptive Deep Network Template (ADNT) is defined whose parameters are …

Video-based Face Recognition (VFR) can be converted to the matching of two image sets
containing face images captured from each video. For this purpose, we propose to bridge …

Existing multi-model approaches for image set classification extract local models by
clustering each image set individually only once, with fixed clusters used for matching with …