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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Aktualisiert 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.

Zitieren als

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

Kompatibilität der MATLAB-Version
Erstellt mit R2019b
Kompatibel mit R2019b und späteren Versionen
Plattform-Kompatibilität
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Version Veröffentlicht Versionshinweise
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