Amazon Rekognition | Facial Analysis Flashcards
How can I give feedback to Rekognition to improve its Unsafe Content Detection?
Facial Analysis
Amazon Rekognition | Machine Learning
Please send us your requests through AWS Customer Support. Amazon Rekognition continuously expands the types of inappropriate content detected based on customer feedback. It usually takes 6-8 weeks to add new types of explicit or suggestive adult content. Please note that illegal content (such as child pornography) will not be accepted through this process.
What is Facial Analysis?
Facial Analysis
Amazon Rekognition | Machine Learning
Facial analysis is the process of detecting a face within an image and extracting relevant face attributes from it. Amazon Rekognition Image takes returns the bounding box for each face detected in an image along with attributes such as gender, presence of sunglasses, and face landmark points. Rekognition Video will return the faces detected in a video with timestamps and, for each detected face, the position and a bounding box along with face landmark points.
What face attributes can I get from Amazon Rekognition?
Facial Analysis
Amazon Rekognition | Machine Learning
Amazon Rekognition returns the following facial attributes for each face detected, along with a bounding box and confidence score for each attribute:
Gender
Smile
Emotions
Eyeglasses
Sunglasses
Eyes open
Mouth open
Mustache
Beard
Pose
Quality
Face landmarks
What is face pose?
Facial Analysis
Amazon Rekognition | Machine Learning
Face pose refers to the rotation of a detected face on the pitch, roll, and yaw axes. Each of these parameters is returned as an angle between -180 and +180 degrees. Face pose can be used to find the orientation of the face bounding polygon (as opposed to a rectangular bounding box), to measure deformation, to track faces accurately, and more.
What is face quality?
Facial Analysis
Amazon Rekognition | Machine Learning
Face quality describes the quality of the detected face image using two parameters: sharpness and brightness. Both parameters are returned as values between 0 and 1. You can apply a threshold to these parameters to filter well-lit and sharp faces. This is useful for applications that benefit from high-quality face images, such as face comparison and face recognition.
What are face landmarks?
Facial Analysis
Amazon Rekognition | Machine Learning
Face landmarks are a set of salient points, usually located on the corners, tips or mid points of key facial components such as the eyes, nose, and mouth. Amazon Rekognition DetectFaces API returns a set of face landmarks that can be used to crop faces, morph one face into another, overlay custom masks to create custom filters, and more.
How many faces can I detect in an image?
Facial Analysis
Amazon Rekognition | Machine Learning
You can detect up to 100 faces in an image using Amazon Rekognition.
How is Facial Analysis different for video analysis?
Facial Analysis
Amazon Rekognition | Machine Learning
With Rekognition Video, you can locate faces across a video and analyze face attributes, such as whether the face is smiling, eyes are open, or showing emotions. Rekognition Video will return the detected faces with timestamps and, for each detected face, the position and a bounding box along with landmark points such as left eye, right eye, nose, left corner of the mouth, and right corner of the mouth. This position and time information can be used to easily track user sentiment over time and deliver additional functionality such as automatic face frames, highlights, or crops.
