Detect, Analyze, and Compare Faces with Amazon Rekognition

Implementation

• Enter the Amazon Rekognition console

  Open the AWS Management Console, so you can keep this step-by-step guide open. When the screen loads, enter your user name and password to get started. Then type Rekognition in the search bar and select Rekognition to open the service console.
  

  

• Analyze faces

  In this step, you will use the facial analysis feature in Amazon Rekognition to see the detailed JSON response you can receive from analyzing one image.
  

  a) To start, select Facial analysis in the panel navigation on the left. This feature allows you to analyze faces in an image and receive a JSON response.

  

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  b) Open and save the first sample image for this tutorial here.
  

  

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  c) Click the orange Upload button and select the sample image you just saved.
  

  

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  d) Notice that under the Results dropdown, you can click through and see quick results for each face that was detected.

  

   

  e) Click on the Response dropdown to see the JSON results. Notice that under the emotions results, there are numerous detected emotions. Happy has a 99.98% confidence rating.

   

  As a developer, detecting emotions in images and videos makes it possible to quickly catalog a digital library by emotion. Another use case for detecting emotions is to amplify ad targeting so users receive a personalized experience tailored to the current emotion.
  

  

  

• Compare faces
  In this step, you will use the face comparison feature to see the detailed JSON response from comparing two different images that don't match.

  a) Select Face comparison in the panel navigation on the left.
  

  

   

  b) Open and save the second sample image for this tutorial here.
  

  

   

  c) Click on the orange Upload button for the reference face and select the image you just saved.

  

   

  d) Click on the orange Upload button for the comparison face and select our first sample image we used in step 2.

  

   

  e) Notice that in Results dropdown you can see that our reference wasn’t a match for any of the detected faces in our comparison faces image.
  

  

   

  f) Click on the Response dropdown to see the JSON results. Notice that the “Similarity” score for each of the detected faces never exceeds 1. The similarity score ranges from 1-100 and the threshold can be adjusted when using the API.

  As a developer, comparing faces at scale can be used in applications to track persons of interest, create a face-based employee verification system, or provide a VIP experience to guests staying at a hospitality venue.
  

  

• Compare faces (again)
  In this step, you will use the face comparison feature to see the detailed JSON response from comparing two different images that have a match.
  

  a) Open and save the third and final sample image for this tutorial here.
  

  

   

  b) Click on the orange Upload button for the reference face and select the image you just saved.

  

   

  c) Notice that the reference face that was compared to our other photo detected a 99% similarity score and detected that all other faces were not a match.

  

   

  d) Click on the Response dropdown to see the details of each comparison.