Learning Structured Visual Detectors from User Input at Multiple Levels

@article{Jaimes2001LearningSV,
  title={Learning Structured Visual Detectors from User Input at Multiple Levels},
  author={Alejandro Jaimes and Shih-Fu Chang},
  journal={Int. J. Image Graphics},
  year={2001},
  volume={1},
  pages={415-444}
}
In this paper, we propose a new framework for the dynamic construction of structured visual object/scene detectors for content-based retrieval. In the Visual Apprentice, a user defines visual object/scene models via a multiple-level definition hierarchy: a scene consists of objects, which consist of object-parts, which consist of perceptual-areas, which consist of regions. The user trains the system by providing example images/videos and labeling components according to the hierarchy she… CONTINUE READING
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