We present a two-layer generative model for sport video mining that is composed of a two-layer observation model. The first layer is the Gaussian mixture model (GMM) using framew...
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Many sports videos such as archery, diving and tennis have repetitive structure patterns. They are reliable clues to generate highlights, summarization and automatic annotation. I...
Situated models of meaning ground words in the non-linguistic context, or situation, to which they refer. Applying such models to sports video retrieval requires learning appropri...
The development of mid-level concepts helps to bridge the gap between low-level feature and high-level semantics in video analysis. Most existing work combines the customized mid-...