We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
Our participation in TREC 2003 aims to adapt the use of the DFR (Divergence From Randomness) models with Query Expansion (QE) to the robust track and the topic distillation task o...
Giambattista Amati, Claudio Carpineto, Giovanni Ro...
In this paper, we define the problem of topic-sentiment analysis on Weblogs and propose a novel probabilistic model to capture the mixture of topics and sentiments simultaneously....
Qiaozhu Mei, Xu Ling, Matthew Wondra, Hang Su, Che...
We explore the hypothesis that it is possible to obtain information about the dynamics of a blog network by analysing the temporal relationships between blogs at a semantic level, ...
Temporal consistency is ubiquitous in video data, where temporally adjacent video shots usually share similar visual and semantic content. This paper presents a thorough study of ...