A New Way to Age Estimation for RGBD Images based on a New Face Detection and Extraction Method for Depth Images

This repository implements an age estimation pipeline for RGB (Color) and Depth images. The system combines face extraction, edge detection, entropy calculation, and normalization to predict an individual's age based on both modalities. The methodology is inspired by the paper "A New Way to Age Estimation for RGB-D Images based on a New Face Detection and Extraction Method for Depth Images".

• Link to the paper:
• https://www.mecs-press.org/ijigsp/ijigsp-v10-n11/v10n11-2.html

Features

• Face Detection and Extraction:
  • For depth images: A novel method using standard deviation filtering and ellipse fitting.
  • For color images: Viola-Jones algorithm is used to identify the face region.
• Entropy and Edge Detection:
  • Entropy is calculated from the depth image to capture randomness.
  • Sobel edge detection is applied to the color image for feature extraction.
• Age Normalization:
  • Combines entropy and edge values to estimate age, normalized between the youngest and oldest samples in the dataset.

• Please cite below:

Mousavi, Seyed Muhammad Hossein. "A new way to age estimation for rgb-d images, based on a new face detection and extraction method for depth images." International Journal of Image, Graphics and Signal Processing 10.11 (2018): 10.

• DOI:
• https://www.mecs-press.org/ijigsp/ijigsp-v10-n11/v10n11-2.html