Predicting Ideal Hairstyles Based on Face Shape | Beauty Machine Learning

QOVES Studio
29 Apr 202114:06

TLDRThis video discusses how machine learning can predict ideal hairstyles based on an individual's face shape. It explains that facial identification systems can recommend hairstyles by evaluating facial features such as eye shape, jaw shape, and overall facial structure. The video outlines five main face shapes: oblong, round, oval, square, and heart, each with specific hairstyles that best complement them. A 2018 paper by Pasupa et al is mentioned, which uses a support vector machine to recommend hairstyles based on length, style, fringe, and layering. The technology can 'map' hairstyles onto the face using reference points related to the forehead, chin, and cheekbones. The video also touches on the issue of ethnic bias in AI and the importance of including diverse racial groups in training datasets for more accurate and inclusive results. The summary emphasizes the potential of AI in personalizing beauty recommendations and the ongoing efforts to improve its inclusivity and accuracy.

Takeaways

  • 🧑‍🔬 Facial identification systems use machine learning to recommend hairstyles based on facial morphology.
  • 👁 Ocular morphology, jaw shape, and cheekbones are considered to predict which features will suit an individual's face.
  • 📊 A support vector machine, as described in a 2018 paper by Pasupa et al, recommends hairstyles based on scientific aesthetics evidence.
  • 📏 Face shapes are categorized into five main types: oblong, round, oval, square, and heart, each with distinct characteristics.
  • 💡 Oblong faces, like those of Sarah Jessica Parker and Alexa Chung, are long and have equal width along the forehead, cheeks, and jawline.
  • 🌟 Round faces, exemplified by Jennifer Lawrence, are circular with the widest part being the cheekbones and a significantly curved chin.
  • 🍎 Oval faces, such as Blake Lively's, are longer than wide with the cheekbones as the widest part.
  • 🔲 Square faces, like Cameron Diaz's, have equal height and width with very straight sides and sharp features.
  • ❤️ Heart shaped faces are widest at the forehead and have a pointed chin, often with a widow's peak.
  • 📚 The system uses a facial shape recognition classifier trained on 1000 faces to identify and recommend hairstyles.
  • 🌐 Ethnic bias is acknowledged, and efforts are made to include more racial groups for a more inclusive AI tool.
  • 📈 The technology maps hairstyles onto the face using specific reference points related to facial features for personalized recommendations.

Q & A

  • How do machine learning systems predict the most complimentary hairstyles for an individual's facial shape?

    -Machine learning systems use basic information from facial morphology to predict the most suitable hairstyles. They evaluate aspects like ocular morphology, jaw shape, and overall facial shape, defined by a facial recognition classifier.

  • What are the five main categories of face shapes identified by the facial identification systems?

    -The five main categories are oblong (rectangular), round, oval, square, and heart shapes.

  • How does the facial shape of oblong?

    -An oblong face shape is characterized by a long, thin face with equal width across the forehead, cheeks, and jawline, and a slightly curved chin.

  • What are some notable features of a round face shape?

    -A round face has a circular shape with the cheekbones being the widest part of the face, a significantly curved chin, and sides of the face that curve outwards.

  • What are the key characteristics of an oval face shape?

    -An oval face shape has a tall forehead, cheekbones as the widest part, and a face that is longer than it is wide.

  • How does the machine learning system recommend hairstyles for different face shapes?

    -The system recommends hairstyles based on the length (pixie, short, medium, long), style (straight, wavy, or a mix), fringe (none, straight, or side-swept), and layering (layered or not) of the hair.

  • What are the main attributes considered by the Support vector machine for hairstyle recommendations?

    -The main attributes are hair length, style, fringe, and whether the hair should be layered or not.

  • How does the technology map the recommended hairstyle onto the face?

    -The technology uses specific reference points related to the forehead, chin, and cheekbones to map the hairstyle onto the face.

  • What are the challenges in developing AI technology for predicting hairstyles?

    -One of the main challenges is the role of ethnic bias due to a lack of diverse training data, which can limit the inclusivity and accuracy of the AI tool.

  • How does the facial shape recognition classifier developed in the research work?

    -The facial shape recognition classifier works by coding characteristics for each face shape, training the system using a dataset of faces, and employing a landmark localization technique called the ‘Active Appearance Model’ to calculate geometric features representing face shape.

  • What are the limitations acknowledged in the current machine learning field regarding beauty and facial aesthetics?

    -The limitations include the potential for ethnic bias and the need for more diverse and inclusive datasets to better represent various races and hair types.

Outlines

00:00

💡 Predicting the Perfect Hairstyle for Your Face Shape

This paragraph discusses how facial identification systems and machine learning can recommend hairstyles based on an individual's facial shape. It explains that by evaluating features like ocular morphology, jaw shape, and overall facial shape, these systems can predict which hairstyles will be most flattering. The paragraph references a 2018 paper by Pasupa et al., which details a support vector machine that recommends hairstyles based on scientific aesthetics evidence. It also describes the process of dividing face shapes into five main categories: oblong, round, oval, square, and heart-shaped, providing examples of celebrities for each shape.

05:01

🧑‍🔬 Machine Learning and Facial Shape Recognition

The second paragraph delves into the scientific evidence supporting the idea that certain hairstyles complement specific face shapes. It outlines the process of using geometrical rules and aesthetics guidelines to determine which hairstyles are most suitable. The technology behind this involves coding a facial shape recognition classifier and training the system using a diverse dataset. The paragraph also discusses the Active Appearance Model, which analyzes vital points on the face to calculate geometric features. It addresses the issue of ethnic bias in AI and the use of the Fairface dataset to mitigate this bias. The paragraph concludes with the attributes the support vector machine considers when recommending hairstyles: length, style, fringe, and layering.

10:04

💇‍♀️ Recommendations for Different Face Shapes

The final paragraph provides specific hairstyle recommendations for each of the five main face shapes. For round faces, it suggests medium-length hair with a side-swept fringe to add height. Square faces are recommended to have hairstyles that soften their sharp features, with a medium to long hair length and a side-swept fringe. Oval faces, being versatile, can pull off a variety of hairstyles without needing to add extra height. Oblong or rectangular faces are advised to opt for curly or short hair to reduce the perceived height and create a fuller look. Lastly, heart-shaped faces are suggested to maintain width with a side-swept fringe and long, layered hair, which can be either curly or straight. The paragraph emphasizes the importance of considering the skull's morphology and the relationship between facial features when recommending hairstyles.

Mindmap

Keywords

💡Facial Identification Systems

Facial identification systems are technologies that use the unique features of a person's face to identify or categorize them. In the context of this video, these systems are used to recommend hairstyles that are most flattering for an individual's facial shape. This is done by analyzing various aspects of facial morphology, such as the size and shape of the eyes, jaw shape, and cheekbones.

💡Machine Learning

Machine learning is a type of artificial intelligence that allows systems to learn from data and improve their performance over time without being explicitly programmed. In this video, machine learning systems are used to predict the best hairstyles for individuals based on their facial features. The system uses facial morphology information to make objective recommendations, which is crucial for personalizing beauty advice.

💡Facial Morphology

Facial morphology refers to the physical form and structure of the face, including the size, shape, and composition of facial features. The video discusses how machine learning systems evaluate facial morphology, such as the ocular morphology (size and shape of the eyes), jaw shape, and cheekbones, to determine the most suitable hairstyles for a person's face.

💡Facial Shape Classifier

A facial shape classifier is a tool or algorithm that categorizes faces into different shapes based on their characteristics. In the video, it is mentioned that face shapes can be divided into five main categories: oblong, round, oval, square, and heart. This classification is essential for the machine learning system to recommend hairstyles that best suit each face shape.

💡Support Vector Machine (SVM)

A support vector machine is a machine learning model used for classification and regression analysis. In the context of the video, a SVM is constructed to recommend a chosen hairstyle for a user based on scientific aesthetics evidence. It helps in mapping the hairstyle onto the face using specific reference points related to the forehead, chin, and cheekbones.

💡Ocular Morphology

Ocular morphology pertains to the study of the structure and form of the eyes, including their size, shape, and positioning in relation to the skull. The video explains that this feature is considered when predicting hairstyles, as the eyes are a significant part of the facial composition and can influence the overall balance and aesthetics of a hairstyle.

💡Jaw Shape

Jaw shape is a facial feature that refers to the structure and outline of the jawline. It is one of the critical elements in facial morphology that the machine learning system evaluates to recommend hairstyles. The video mentions that the jaw shape complements the teeth and cheekbones and is a determinant in finding a hairstyle that suits an individual's face.

💡Cheekbones

Cheekbones are the bony prominences on the sides of the face, which play a role in the overall balance and aesthetics of an individual's face. In the video, they are discussed as a key component in facial morphology that influences the choice of hairstyles. For instance, the widest part of the face, such as the cheekbones, is a factor in determining if a face is round or oval-shaped.

💡Hairstyle Recommendations

The video outlines how machine learning systems provide hairstyle recommendations based on the individual's facial shape. It includes attributes such as length (pixie, short, mid, long), style (straight, wavy), fringe (none, straight, side swept), and layering. These recommendations are tailored to enhance the specific features of the face and create a harmonious look.

💡Ethnic Bias in AI

Ethnic bias in AI refers to the unfairness or prejudice in artificial intelligence systems due to a lack of diversity in the training data. The video acknowledges this issue, noting that the current face shape classifier in development uses the Fairface dataset, which includes equal weightings of seven racial groups to minimize such bias. This is an important consideration to ensure that AI tools are inclusive and effective for a wide range of individuals.

💡Active Appearance Model (AAM)

The Active Appearance Model is a technique used in computer vision for tracking and recognizing human faces. It is mentioned in the video as a method for localizing landmarks on the face and analyzing skin pigmentation to separate the hair from the forehead. This technology is crucial for accurately determining the geometric features that represent face shape, which in turn helps in making precise hairstyle recommendations.

Highlights

Machine learning can predict the most complimentary hairstyles based on an individual's facial shape.

Facial identification systems evaluate ocular morphology, jaw shape, and overall facial shape to recommend hairstyles.

A support vector machine recommends hairstyles based on scientific aesthetics evidence.

Face shape can be divided into five main categories: oblong, round, oval, square, and heart.

Oblong faces, like those of Sarah Jessica Parker and Alexa Chung, are characterized by equal width along the forehead, cheeks, and jawline.

Round faces, such as Jennifer Lawrence's, have the widest part at the cheekbones with a significantly curved chin.

Oval faces, typified by Blake Lively, have a tall forehead and are longer than they are wide with the cheekbones as the widest part.

Square faces, like Cameron Diaz's, have the same overall height and width with very straight sides and sharp features.

Heart-shaped faces, with the widest part being the forehead and a pointed chin, often have a widow's peak hairline.

Beyond the five main categories, there are additional shapes like diamond and triangular faces.

Aesthetic guidelines provide geometrical rules to objectively determine which hairstyles work best for each face shape.

The facial shape recognition classifier is trained using 1000 faces from a Google image search.

The Active Appearance Model technology calculates geometric features to represent face shape by examining vital points on the face.

Ethnic bias in AI technology is a significant issue, which the paper acknowledges and plans to address in future work.

The Support Vector Machine recommends hairstyles based on length, style, fringe, and layering attributes.

For round faces, a medium-length hairstyle with a side-swept fringe is suggested to add height and avoid emphasizing roundness.

Square faces benefit from hairstyles that soften the sharp features and add height, avoiding strong, straight fringes.

Oval faces are versatile and can accommodate a wide variety of hairstyles without needing to add extra height.

Oblong faces are recommended to have curly or short hair to reduce the perceived height and create a fuller look.

Heart-shaped faces should maintain width with a side-swept fringe and opt for long, layered hair, which can be curly or straight.