Corpus ID: 15857769

Context Forest for efficient object detection with large mixture models

@article{Modolo2015ContextFF,
  title={Context Forest for efficient object detection with large mixture models},
  author={Davide Modolo and A. Vezhnevets and V. Ferrari},
  journal={ArXiv},
  year={2015},
  volume={abs/1503.00787}
}
  • Davide Modolo, A. Vezhnevets, V. Ferrari
  • Published 2015
  • Computer Science
  • ArXiv
  • We present Context Forest (ConF), a technique for predicting properties of the objects in an image based on its global appearance. Compared to standard nearest-neighbour techniques, ConF is more accurate, fast and memory efficient. We train ConF to predict which aspects of an object class are likely to appear in a given image (e.g. which viewpoint). This enables to speed-up multi-component object detectors, by automatically selecting the most relevant components to run on that image. This is… CONTINUE READING

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