Object classification by fusing SVMs and Gaussian mixtures

  title={Object classification by fusing SVMs and Gaussian mixtures},
  author={Thomas Deselaers and Georg Heigold and Hermann Ney},
  journal={Pattern Recognition},
We present a new technique that employs support vector machines (SVMs) and Gaussian mixture densities (GMDs) to create a generative/discriminative object classification technique using local image features. In the past, several approaches to fuse the advantages of generative and discriminative approaches were presented, often leading to improved robustness and recognition accuracy. Support vector machines are a well known discriminative classification framework but, similar to other… CONTINUE READING
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The PASCAL Visual Object Classes Challenge 2006 (VOC2006) Results

  • M. Everingham, A. Zisserman, C.K.I. Williams, L. Van Gool
  • Technical report, PASCAL Network of Excellence,
  • 2006
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