Local Descriptors Encoded by Fisher Vectors for Person Re-Identification
Abstract
This paper proposes a new descriptor for person re-identification building on the recent advances of Fisher Vectors. Specifically, a simple vector of attributes consisting in the pixel coordinates, its intensity as well as the first and second-order derivatives is computed for each pixel of the image. These local descriptors are turned into Fisher Vectors before being pooled to produce a global representation of the image. The so-obtained Local Descriptors encoded by Fisher Vector (LDFV) have been validated through experiments on two person re-identification benchmarks (VIPeR and ETHZ), achieving state-of-the-art performance on both datasets.
Cite
Text
Ma et al. "Local Descriptors Encoded by Fisher Vectors for Person Re-Identification." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33863-2_41Markdown
[Ma et al. "Local Descriptors Encoded by Fisher Vectors for Person Re-Identification." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/ma2012eccv-local/) doi:10.1007/978-3-642-33863-2_41BibTeX
@inproceedings{ma2012eccv-local,
title = {{Local Descriptors Encoded by Fisher Vectors for Person Re-Identification}},
author = {Ma, Bingpeng and Su, Yu and Jurie, Frédéric},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {413-422},
doi = {10.1007/978-3-642-33863-2_41},
url = {https://mlanthology.org/eccv/2012/ma2012eccv-local/}
}