Titlebook: Exploration of Visual Data; Xiang Sean Zhou,Yong Rui,Thomas S. Huang Book 2003 Springer Science+Business Media New York 2003 Boosting.Comp

無可爭辯

Probabilistic Local Structure Models,Small, local evidences can reveal a great deal in an image.

Tincture

Future Research Directions,Content-based exploration of visual data is a relatively new research area, with many promising future research directions. To extend and continue the research carried out in this book, the emphasis may be put on the following challenging topics

Barrister

Constructing Table-of-Content for Videos,portant role that Table-of-Content (ToC) plays in a book, in this chapter we introduce the concept of ToC in the video domain. Some existing approaches implicitly use the ToC, but are mainly limited to low-level entities (e.g. shots and key frames). The drawbacks are that low-level structures (1) co

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Indelible

Relevance Feedback for Visual Data Retrieval,(or .). Two issues arise: one is the effectiveness of the representation, i.e., to what extent can the meaningful contents of the media be represented in these vectors? The other is the selection of a . during the retrieval process. This is an important issue because the similarity metric dynamicall

Infantry

chondromalacia

禮節(jié)

Relevance Feedback for Visual Data Retrieval,y depends upon the user and the user defined query class, which are unknown .. In the following, we focus our attention on the second issue, i.e., the on-line learning problem for content-based multimedia information retrieval.

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