Amazon Rekognition | Face Comparison

Question 1

In addition to Video resolution, what else can affect the quality of the Rekognition Video APIs?

Face Comparison

Amazon Rekognition | Machine Learning

Answer 1

Besides video resolution, the quality and representative faces, part of the face collections to search, has major impact. Using multiple face instances per person with variations like beard, glasses, poses (profile and frontal) will significantly improve the performance. Typically very fast moving people and blurred videos may experience lower quality.

Question 2

What is Face Comparison?

Face Comparison

Amazon Rekognition | Machine Learning

Answer 2

Face Comparison is the process of comparing one face to one or more faces to measure similarity. Using the CompareFaces API, Amazon Rekognition Image lets you measure the likelihood that faces in two images are of the same person. The API compares a face in the source input image with each face detected in the target input image and returns a similarity score for each comparison. You also get a bounding box and confidence score for each face detected. You can use face comparison to verify a person’s identity against their personnel photo on file in near real-time.

Question 3

Can I use a source image with more than one face?

Face Comparison

Amazon Rekognition | Machine Learning

Answer 3

Yes. If the source image contains multiple faces, CompareFaces detects the largest face and uses it to compare with each face detected in the target image.