Face, Age and Emotion Detection

Demo for face, age and emotion detection (all using Deep Learning) and leveraging the capability to import Caffe models in MATLAB.
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Updated 21 Apr 2020

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Demo for performing face, age and emotion detection leveraging pretrained networks from research and the capability to import Caffe models in MATLAB.

Note: If your license includes MATLAB Coder and GPU Coder, you will be able to improve inference performance by generating CUDA code (in the form of MEX files) for each of the predict functions. Review README file for instructions.

References to pretrained models:
[1] Abars, Face Search VGG16, (2018). GitHub repository, https://github.com/abars/FaceSearchVGG16
[2] Rasmus Rothe, Radu Timofte and Luc Van Gool, (2016). Deep expectation of real and apparent age from a single image without facial landmarks. International Journal of Computer Vision (IJCV).
[3] Jia, Yangqing, et al., (2014). "Caffe: Convolutional architecture for fast feature embedding." Proceedings of the 22nd ACM international conference on Multimedia. ACM.

Cite As

Lucas García (2024). Face, Age and Emotion Detection (https://www.mathworks.com/matlabcentral/fileexchange/71819-face-age-and-emotion-detection), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux
Categories
Find more on Recognition, Object Detection, and Semantic Segmentation in Help Center and MATLAB Answers

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Version Published Release Notes
2.0.1

- Updated MATLAB Release Compatibility

2.0.0

- Enhancing detection and tracking using computer vision techniques
- Enhanced emotion detection
- Included version to deploy on Jetson boards

1.0.0