Partitioning a video sequence into shots is the first step toward video-content analysis and
content-based video browsing and retrieval. A video shot is defined as a series of interrelated …

Over the past two decades, a large amount of research effort has been devoted to
developing algorithms that generate recommendations. The resulting research progress has …

This paper looks into a new direction in video content analysis - the representation and
modeling of affective video content . The affective content of a given video clip can be defined as …

Key frames and previews are two forms of a video abstract, widely used for various applications
in video browsing and retrieval systems. We propose in this paper a novel method for …

Cross-modal retrieval aims to enable flexible retrieval experience across different modalities
(eg, texts vs. images). The core of cross-modal retrieval research is to learn a common …

This paper considers how we feel about the content we see or hear. As opposed to the cognitive
content information composed of the facts about the genre, temporal content structures …

We present a newly developed strategy for automatically segmenting movies into logical
story units. A logical story unit can be understood as an approximation of a movie episode, …

In this paper we tackle the problem of recommendation in the scenarios with binary relevance
data, when only a few (k) items are recommended to individual users. Past work on …

A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise
learning-to-rank algorithm with matrix factorization (MF). A ranked list of items is …

… On the basis of the above, Hanjalic computed the variancebased feature component ½(k)
of the discriminative function as the relative change of intensity variance in the frame from the …