Covariance Descriptor based on Bio-inspired Features for Person Re-identification and Face Verification

Bingpeng Ma 1 Yu Su 2 Frédéric Jurie 2, *
* Corresponding author
1 image
School of Computer and Control Engineering
2 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : Avoiding the use of complicated pre-processing steps such as accurate face and body part segmentation or image normalization, this paper proposes a novel face/person image representation which can properly handle background and illumination variations. Denoted as gBiCov, this representation relies on the combination of Biologically Inspired Features (BIF) and Covariance descriptors. More precisely, gBiCov is obtained by computing and encoding the difference between BIF features at different scales. The distance between two persons can then be efficiently measured by computing the Euclidean distance of their signatures, avoiding some time consuming operations in Riemannian manifold required by the use of Covariance descriptors. In addition, the recently proposed KISSME framework is adopted to learn a metric adapted to the representation. To show the effectiveness of gBiCov, experiments are conducted on three person re-identification tasks (VIPeR, i-LIDS and ETHZ) and one face verification task (LFW), on which competitive results are obtained. As an example, the matching rate at rank 1 on the VIPeR dataset is of 31.11%, improving the best previously published result by more than 10%.
Document type :
Journal articles
Complete list of metadatas

Cited literature [52 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01009958
Contributor : Frederic Jurie <>
Submitted on : Thursday, June 19, 2014 - 4:10:05 AM
Last modification on : Thursday, February 7, 2019 - 5:47:14 PM
Long-term archiving on : Friday, September 19, 2014 - 10:47:01 AM

File

14_IMAVIS_REID.pdf
Files produced by the author(s)

Identifiers

Citation

Bingpeng Ma, Yu Su, Frédéric Jurie. Covariance Descriptor based on Bio-inspired Features for Person Re-identification and Face Verification. Image and Vision Computing, Elsevier, 2014, 32 (6-7), pp.379-390. ⟨10.1016/j.imavis.2014.04.002⟩. ⟨hal-01009958⟩

Share

Metrics

Record views

478

Files downloads

1095