Abstract
As re-occurring compositions of visual data, visual patterns exist in complex spatial structures and diverse feature views of image and video data. Discovering visual patterns is of great interest to visual data analysis and recognition. Many methods have been proposed to address the problem of visual pattern discovery during the dozen years. In this chapter, we start with an overview of the visual pattern discovery problem and then discuss the major progress of spatial and feature co-occurrence pattern discovery.
| Original language | English |
|---|---|
| Pages (from-to) | 1-13 |
| Number of pages | 13 |
| Journal | SpringerBriefs in Computer Science |
| Volume | 0 |
| Issue number | 9789811048395 |
| DOIs | |
| State | Published - 2017 |
Keywords
- Bottom-up methods
- Co-training
- Feature co-occurrence pattern discovery
- Multiple kernel learning
- Spatial co-occurrence pattern discovery
- Subpace learning
- Top-down methods
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