Multiplicative kernels: Object detection, segmentation and pose estimation

  title={Multiplicative kernels: Object detection, segmentation and pose estimation},
  author={Quan Yuan and Ashwin Thangali and Vitaly Ablavsky and Stan Sclaroff},
  journal={2008 IEEE Conference on Computer Vision and Pattern Recognition},
Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and within-class classification of the foreground class (pose estimation) can be jointly learned in a multiplicative form of two kernel functions. One kernel measures similarity for foreground-background classification. The other kernel accounts for latent factors that control within-class variation and implicitly enables… CONTINUE READING
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