DATASET
Keypoints-labeling of facial points on people's photos. The dataset solves the tasks of face recognition and emotion analysis

Facial Keypoints Detection

Ability of a machine to interpret, analyze, and understand visual data
Computer Vision
Process of identifying or verify a person identity using facial features
Facial Recognition
Process of identifying and classifying human emotional states
Emotion Recognition
Highlighting objects in photos to train systems to recognize and interpret them
Data Labeling
1500
images
2 weeks
project duration
9.4
usability
Technical
specifications
Each face is placed using 15 keypoints
Photos and selfies of people are collected using parsing and crowdsourcing
Labeled Keypoints:
Left eye, the closest point to the nose
Left eye, the closest point to the left ear
Right eye, the closest point to the nose
Right eye, pupil's center
Left eye, pupil's center
Right eye, the closest point to the right ear
Left eyebrow, the closest point to the left ear
Right eyebrow, the closest point to the nose
Right eyebrow, the closest point to the right ear
Left eyebrow, the closest point to the nose
Mouth, left corner point
Nose, center
Mouth, right corner point
Mouth, the highest point in the middle
Mouth, the lowest point in the middle
Each image from FKP folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the key points. For each point, the x and y coordinates are provided
And there is a Presumed_Location attribute, indicating whether the point is presumed or accurately defined
Our services
Data Collection of tens of thousands of photos with metadata of gender, age of people and country of residence using crowdsourcing of tens of thousands of photos with metadata of gender, age of people and country of residence
Facial Keypoint Detection of required facial points with attributes of the assumed location
Classification of emotions, face orientation, Bounding Box labelling, as well as semantic segmentation for people's selfies
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