Face Detection engines in the Veritone cognitive engine ecosystem detect human faces in video and locate them with bounding boxes.
A face detection engine determines whether any face is present, but it does not identify the face or match it to other data, like face recognition. Face detection and face recognition engines can be used in concert.
Face Detection Features:
Face Attribute & Emotion Prediction
Detect human faces including machine learning-based predictions of visual age, gender, attention, and emotion including neutral, anger, contempt, disgust, fear, happiness, sadness, and surprise.
Broad Data Source Support
Locate faces in videos and photos from sources such as body cameras, CCTV, booking photos, TV broadcasts, movies, mobile phone video, and more.
Identify where in a frame and when faces are detected within files and data streams quickly with searchable face detection engine output via API and Veritone applications.
Near Real-Time Processing
Process image and video files in near real-time for use cases requiring near immediate face detection.
Files or Stream Support
Detect faces in short-form or long-form videos in recordings, streamed recordings, or live data streams.
Deploy in a new or integrate into an existing application in the cloud via aiWARE GraphQL APIs, or with a subset that can be deployed on-premise via a Docker container. Learn more.
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Leverage advanced face detection machine learning algorithms from the Veritone managed cognitive engine ecosystem — including algorithms from Veritone, niche providers, and industry giants.