Along with the explosive growth of multimedia data, automatic multimedia tagging has
attracted great interest of various research communities, such as computer vision …

The exponential growth of technology has resulted in a profusion of advanced imaging
devices and eases internet accessibility, leading to an increase in the creation and use of …

Video semantic recognition usually suffers from the curse of dimensionality and the absence
of enough high-quality labeled instances, thus semisupervised feature selection gains …

In this paper, we study the challenging problem of categorizing videos according to high-
level semantics such as the existence of a particular human action or a complex event …

We propose a novel reconstruction-based transfer learning method called latent sparse
domain transfer (LSDT) for domain adaptation and visual categorization of heterogeneous …

This chapter provides an accessible introduction for point processes, and especially Hawkes
processes, for modeling discrete, inter-dependent events over continuous time. We start by …

We propose a visual event recognition framework for consumer videos by leveraging a large
amount of loosely labeled web videos (eg, from YouTube). Observing that consumer videos …

Recognizing visual content in unconstrained videos has become a very important problem
for many applications. Existing corpora for video analysis lack scale and/or content diversity …

The rapid growth of consumer videos requires an effective and efficient content
summarization method to provide a user-friendly way to manage and browse the huge …

Recent work has demonstrated the effectiveness of domain adaptation methods for
computer vision applications. In this work, we propose a new multiple source domain …