The proliferation of MP3 players and the exploding amount of digital music content call for
novel ways of music organization and retrieval to meet the ever-increasing demand for easy …

Images can convey rich semantics and induce various emotions in viewers. Recently, with
the rapid advancement of emotional intelligence and the explosive growth of visual data …

Music genre classification is one of the sub-disciplines of music information retrieval (MIR)
with growing popularity among researchers, mainly due to the already open challenges …

The amount of user-generated multimedia content (UGC) has increased rapidly in recent
years due to the ubiquitous availability of smartphones, digital cameras, and affordable …

The rapidly growing corpus of digital audio material requires novel retrieval strategies for
exploring large music collections. Traditional retrieval strategies rely on metadata that …

Capturing videos anytime and anywhere, and then instantly sharing them online, has
become a very popular activity. However, many outdoor user-generated videos (UGVs) lack …

In music mood prediction, regression models are built to predict values on several mood-
representing dimensions such as valence (level of pleasure) and arousal (level of energy) …

Music emotion is an important component in the field of music information retrieval and
computational musicology. Considering the complexity of the state-of-the-art methods and …

Modeling the association between music and emotion has been considered important for
music information retrieval and affective human computer interaction. This paper presents a …

One of the most exciting but challenging endeavors in music research is to develop a
computational model that comprehends the affective content of music signals and organizes …