General structure of the proposed Method
Authors:
Abdelhakim Chergui1, Salim Ouchtati1, Hichem Telli2, Fares Bougourzi3 and Salah Eddine Bekhouche4
- Laboratory of LRES, University of Skikda, Algeria.
- Laboratory of LESIA, University of Biskra, Algeria.
- Laboratory of LTII, University of Bejaia, Algeria.
- Department of Electrical Engineering, University of Djelfa, Algeria.
Abstract:
The automatic verification of kinship is a challenging problem that recently attracted much interest in computer vision, the kinship verification has become an active research field due to its potential applications such as organizing photo albums and images annotation, recognizing resemblances among humans and finding of missing children. In this paper, we propose an approach which takes two images as an input then give kinship result (kinship / non-kinship) as an output.This approach based on the Local Phase Quantization (LPQ) and Local directional pattern (LDP) features descriptors and the ML (Multi-Level) representation for the kinship verification from facial images, this work consists six stages which are : (i) face preprocessing, (ii) features extraction, (iii) face representation (iv) pair features representation and normalization, (v) features selection and (vi) kinship verification. Experiments are conducted on four public databases (Cornell KinFace, UB Kin database, KinFace-I, and KinFace-II). The obtained results are good compared with state-of-the-art approaches.
Please cite as:
@InProceedings{SIGPROMD2018,
author={Chergui, Abdelhakim and Ouchtati, Salim and Telli, Hichem and Bougourzi, Fares and Bekhouche, Salah Eddine},
booktitle={The Second International Workshop on Signal Processing Applied to Rotating Machinery Diagnostics, SIGPROMD’2018},
title={LPQ and LDP Descriptors with ML Representation for Kinship verification},
year={2018},
pages={1-10},
month={Apr}
}
Downloads:
Paper: PDF
Database: KinshipVerification, KinFace_V2, KinFaceW-I and KinFaceW-II
Code: