ML Anthology

Scene Image Categorization and Video Event Detection Using Naive Bayes Nearest Neighbor

Shiv Naga Prasad Vitaladevuni, Pradeep Natarajan, Shuang Wu, Xiaodan Zhuang, Rohit Prasad, Premkumar Natarajan
WACV 2013 pp. 140-147
doi:10.1109/WACV.2013.6475011 /wacv/2013/vitaladevuni2013wacv-scene/

Abstract

We present a detailed study of Naive Bayes Nearest Neighbor (NBNN) proposed by Boiman et al., with application to scene categorization and video event detection. Our study indicates that using Dense-SIFT along with dimensionality reduction using PCA enables NBNN to obtain state-of-the-art results. We demonstrate this on two tasks: (1) scene image categorization on the UIUC 8 Sports Events Image Dataset (obtaining 84.67%) and the MIT 67 Indoor Scene Image Dataset (obtaining 48.84%); and (2) detecting videos depicting certain events of interest on the challenging MED'11 video dataset with only 15 positive training videos per event. We present an extension referred to as sparse-NBNN that constrains the number of training images that can used to match with a given test image for the image-to-class distance computation. Experiments indicate that this improves upon NBNN for handling of imbalanced training data.

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Cite

Text

Vitaladevuni et al. "Scene Image Categorization and Video Event Detection Using Naive Bayes Nearest Neighbor." IEEE/CVF Winter Conference on Applications of Computer Vision, 2013. doi:10.1109/WACV.2013.6475011

Markdown

[Vitaladevuni et al. "Scene Image Categorization and Video Event Detection Using Naive Bayes Nearest Neighbor." IEEE/CVF Winter Conference on Applications of Computer Vision, 2013.](https://mlanthology.org/wacv/2013/vitaladevuni2013wacv-scene/) doi:10.1109/WACV.2013.6475011

BibTeX

@inproceedings{vitaladevuni2013wacv-scene,
  title     = {{Scene Image Categorization and Video Event Detection Using Naive Bayes Nearest Neighbor}},
  author    = {Vitaladevuni, Shiv Naga Prasad and Natarajan, Pradeep and Wu, Shuang and Zhuang, Xiaodan and Prasad, Rohit and Natarajan, Premkumar},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
  year      = {2013},
  pages     = {140-147},
  doi       = {10.1109/WACV.2013.6475011},
  url       = {https://mlanthology.org/wacv/2013/vitaladevuni2013wacv-scene/}
}