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What is Yale face database?

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What is Yale face database?

Synopsis. The Yale Face Database (size 6.4MB) contains 165 grayscale images in GIF format of 15 individuals. There are 11 images per subject, one per different facial expression or configuration: center-light, w/glasses, happy, left-light, w/no glasses, normal, right-light, sad, sleepy, surprised, and wink.

What is Orl dataset?

ORL (Our Database of Faces) The ORL Database of Faces contains 400 images from 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses).

What is Jaffe database?

The JAFFE database contains 213 images of 7 facial expressions (6 basic facial expressions + 1 neutral) posed by 10 Japanese female models. Each image has been rated on 6 emotion adjectives by 60 Japanese subjects. The database was planned and assembled by Michael Lyons, Miyuki Kamachi, and Jiro Gyoba.

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What language is best for image processing?

As per my knowledge and experience, the Matlab and OpenCV win the race of the best language for image processing.

  • Both Matlab and OpenCV are highly efficient programming language for processing the digital images.
  • OpenCV is an open-source programming language.
  • Since OpenCV is open-source, it is free of cost.

Is C++ good for image processing?

C++ is considered to be the fastest programming language, which is highly important for faster execution of heavy AI algorithms. A popular machine learning library TensorFlow is written in low-level C/C++ and is used for real-time image recognition systems.

What is fer2013 dataset?

The FER-2013 dataset was created by gathering the results of a Google image search of each emotion and synonyms​​of​​the​​emotions. The CK+ dataset has a total of 5,876 labeled images of 123 individuals. Each image is labeled with one of seven emotions: happy, sad, angry, afraid, surprise, disgust, and contempt.

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What is facial emotion recognition?

Facial Emotion Recognition (FER) is the technology that analyses facial expressions from both static images and videos in order to reveal information on one’s emotional state.