Hot Event Detection and Summarization by Graph Modeling and Matching

@inproceedings{Peng2005HotED,
  title={Hot Event Detection and Summarization by Graph Modeling and Matching},
  author={Yuxin Peng and Chong-Wah Ngo},
  booktitle={CIVR},
  year={2005}
}
This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally… CONTINUE READING