
Face detection
Written by: Maryam Rajaei

Written by: Maryam Rajaei
Face detection is one of the main elements of all human-centered applications of artificial intelligence. Face is one of the important biometrics in authentication systems. Face detection in real-world images is challenging due to different shapes, orientations, sizes, colors and occlusion due to wearing glasses, hat, and etc. In the last decade, a few promising algorithms have been proposed in this AI field of research. Here, at saiwa face detection service, we provide two methods: 1. Dlib open source cross platform library, and 2. Multitask cascaded convolutional network (MTCNN) method. The first method is known for its performance and low computational time complexity while the second method is more accurate and employs recent advances in the field of deep learning. For more technical details of these methods, please refer to the corresponding white paper. In addition to detecting faces, saiwa face detection service also detects facial features like eyes, eyebrows, nose, mouth and chin. Below you may find a few advantages of using this service:
https://cms.saiwa.ai/uploads/Face_Detection1080link_1_00817bc27a.m4v
Note: Some visuals on this blog post were generated using AI tools.

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