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Home > All Category Datasets > Computer Vision Datasets > 13,587 People - Multi-Race Facial Expression Dataset with 7 Emotions

13,587 People - Multi-Race Facial Expression Dataset with 7 Emotions

facial expression recognition dataset
facial emotion recognition dataset
emotion Recognition dataset
face expression dataset
facial attribute dataset

This dataset contains facial images from 13,587 subjects, including both male and female individuals across diverse age groups from children to elderly people. Young and middle-aged subjects represent the majority of the dataset. For each subject, seven facial images with different expressions were collected. The dataset covers diverse facial poses, emotional states, lighting conditions, and real-world scenarios. The dataset is suitable for facial expression recognition, facial emotion recognition, emotion AI, face analysis, and other computer vision tasks.

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SpecificationsSpecifications
Data size
13,587 people, 7 images for each people, in total 95,109 images
Population distribution
race distribution: 5,448 Asians, 3,514 Caucasians, 3,722 Blacks, and 903 brown (Mexicans) people; gender distribution: male 7,659, female 5,928; age distribution: from child to the elderly, the young people and the middle aged are the majorities
Collection environment
including indoor and outdoor scenes
Collection diversity
different facial postures, different expressions, different light conditions, different scenes
Collection device
cellphone, camera
Image Parameter
the image data format are .jpg, .jpeg, png
Accuracy
the accuracy exceeds 97% based on the accuracy of expressions; the accuracy of expression naming is more than 97%
Sample Sample
  • 13,587 People - Multi-Race Facial Expression Dataset with 7 Emotions
  • 13,587 People - Multi-Race Facial Expression Dataset with 7 Emotions
  • 13,587 People - Multi-Race Facial Expression Dataset with 7 Emotions
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What types of computer vision applications can Nexdata’s datasets support?

Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.

Can Nexdata customize Computer Vision datasets based on our specific requirements?

Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.

How does Nexdata ensure the quality and scalability of its Computer Vision datasets?

Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.

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