Vectors of locally aggregated centers for compact video representation

  title={Vectors of locally aggregated centers for compact video representation},
  author={Alhabib Abbas and Nikos Deligiannis and Yiannis Andreopoulos},
  journal={2015 IEEE International Conference on Multimedia and Expo (ICME)},
We propose a novel vector aggregation technique for compact video representation, with application in accurate similarity detection within large video datasets. The current state-of-the-art in visual search is formed by the vector of locally aggregated descriptors (VLAD) of Jegou et al. VLAD generates compact video representations based on scale-invariant feature transform (SIFT) vectors (extracted per frame) and local feature centers computed over a training set. With the aim to increase… CONTINUE READING
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