L'Oreal (20240249504). SYSTEMS AND METHODS FOR IMPROVED FACIAL ATTRIBUTE CLASSIFICATION AND USE THEREOF simplified abstract

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SYSTEMS AND METHODS FOR IMPROVED FACIAL ATTRIBUTE CLASSIFICATION AND USE THEREOF

Organization Name

L'Oreal

Inventor(s)

Zhi Yu of Toronto (CA)

Yuze Zhang of Scarborough (CA)

Ruowei Jiang of Mississauga (CA)

Jeffrey Houghton of East York (CA)

Parham Aarabi of Richmond Hill (CA)

Frederic Antoinin Raymond Serge Flament of Clichy (FR)

SYSTEMS AND METHODS FOR IMPROVED FACIAL ATTRIBUTE CLASSIFICATION AND USE THEREOF - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240249504 titled 'SYSTEMS AND METHODS FOR IMPROVED FACIAL ATTRIBUTE CLASSIFICATION AND USE THEREOF

The patent application describes a deep learning supervised regression model for facial attribute prediction, with applications in augmented and/or virtual reality interfaces.

  • The model uses deep learning techniques to predict facial attributes from images.
  • Facial effects matching the predicted attributes are selected for application in the interface.
  • The technology enables the modification of images in real-time based on predicted facial attributes.
  • The system can be used to enhance user experiences in virtual reality environments.
  • This innovation has potential applications in gaming, entertainment, and virtual try-on experiences.
      1. Potential Applications:

- Virtual reality gaming - Virtual try-on experiences for cosmetics or accessories - Entertainment industry for special effects in movies or TV shows

      1. Problems Solved:

- Enhances user experiences in virtual reality environments - Provides real-time modification of images based on facial attributes - Enables personalized and interactive applications in augmented reality

      1. Benefits:

- Improved user engagement and immersion in virtual environments - Enhanced customization and personalization in virtual experiences - Efficient and accurate prediction of facial attributes for image modification

      1. Commercial Applications:
        1. Title: Facial Attribute Prediction for Virtual Reality Applications

This technology can be utilized in the gaming industry to create more immersive experiences for players. Additionally, it can be integrated into virtual try-on experiences for retail and cosmetics companies to enhance customer engagement and satisfaction.

      1. Questions about Facial Attribute Prediction:

1. How does the deep learning model accurately predict facial attributes from images? 

  - The deep learning model analyzes facial features and patterns to make predictions based on training data.

2. What are the potential limitations of using facial attribute prediction in virtual reality interfaces? 

  - Some limitations may include accuracy of predictions, processing power required, and privacy concerns.


Original Abstract Submitted

there is described a deep learning supervised regression based model including methods and systems for facial attribute prediction and use thereof. an example of use is an augmented and/or virtual reality interface to provide a modified image responsive to facial attribute predictions determined from the image. facial effects matching facial attributes are selected to be applied in the interface.

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