Object Detection with Discriminatively Trained Part Based Models

@article{Felzenszwalb2009ObjectDW,
  title={Object Detection with Discriminatively Trained Part Based Models},
  author={Pedro F. Felzenszwalb and Ross B. Girshick and David A. McAllester and Deva Ramanan},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2009},
  volume={32},
  pages={1627-1645}
}
We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL data sets. Our system relies on new methods for discriminative training with partially labeled data. We combine a margin… CONTINUE READING
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