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Function
Ref. Model
I/O Data
SubAIMs
JSON MData
Profiles
Ref. Software
Conformance
Performance

1 Functions

The Face Identity Recognition (PAF‑FIR) AIM receives an input Visual Object representing a Face and produces a Bounding Box with the Face and the Identifier of the Face. The PAF‑FIR AIM may also receive an input Visual Geometry of the Visual Scene, an input Time, and a Text Object related to the Visual Object containing the Face:

Receives Text Object Text that is related with the Face to be identified.
Image Visual Object Image containing Face to be identified.
Face Time Time when the face should be identified.
Visual Scene Geometry Of the scene where the Face is located.
Searches for Bounding Boxes That include faces.
Finds Best match Between the Faces and those in a database.
Produces Face Identities Face Instance Identifiers.
Bounding Boxes Bounding Boxes that include faces.

2 Reference Model

Figure 1 depicts the Reference Model of the Face Identity Recognition (PAF‑FIR) AIM.

Face Identity Recognition PAF-FIR AIM

Figure 1 – The Face Identity Recognition (PAF‑FIR) AIM

3 I/O Data

Table 1 specifies the Input and Output Data of the Face Identity Recognition (PAF‑FIR) AIM.

Table 1 – I/O Data of the Face Identity Recognition (PAF‑FIR) AIM

Input Description
Auxiliary Text Object Text with content related to Face ID.
Image Visual Object An image containing the Face to be identified.
Face Time The Time during which the Face should be identified.
Visual Scene Geometry The Geometry of the Scene where the Face is located.
Output Description
Face Identifiers Associate strings to elements belonging to some levels in a hierarchical classification (taxonomy).
Bounding Boxes The box containing the Face identified.

4 SubAIMs

No SubAIMs.

5 JSON Metadata

https://schemas.mpai.community/PAF/V1.6/AIMs/FaceIdentityRecognition.json

6 Profiles

No Profiles.

7 Reference Software

7.1 Disclaimers

  1. This PAF‑FIR Reference Software Implementation is released with the BSD-3-Clause licence.
  2. The purpose of this PAF‑FIR Reference Software is to show a working Implementation of PAF‑FIR, not to provide a ready-to-use product.
  3. MPAI disclaims the suitability of the Software for any other purposes and does not guarantee that it is secure.
  4. Use of this Reference Software may require acceptance of licences from the respective repositories. Users shall verify that they have the right to use any third-party software required by this Reference Software.

7.2 Guide to the PAF‑FIR code

Use of this Reference Software for the PAF‑FIR AI Module is for developers who are familiar with Python, Docker, RabbitMQ, and downloading models from HuggingFace.

PAF‑FIR performs face identity recognition with a pretrained FaceNet model; that is, it identifies the faces in a given number of frames per scene by comparison with a dataset of faces.

The PAF‑FIR Reference Software is found at the MPAI gitlab site. It contains:

  1. src: a folder with the Python code implementing the AIM.
  2. Dockerfile: a Docker file containing only the libraries required to build the Docker image and run the container.
  3. requirements.txt: dependencies installed in the Docker image.
  4. README.md: where to find and save weights of face recognition model FaceNet512.

Library: https://github.com/serengil/deepface

7.3 Acknowledgements

This version of the PAF‑FIR Reference Software has been developed by the MPAI AI Framework Development Committee (AIF‑DC).

8 Conformance Testing

Table 2 provides the Conformance Testing Method for the PAF‑FIR AIM.

If a schema contains references to other schemas, conformance of data for the primary schema implies that any data referencing a secondary schema shall also validate against the relevant schema, if present, and conform with the Qualifier, if present.

Table 2 – Conformance Testing Method for the PAF‑FIR AIM

Receives Text Object Shall validate against Text Object schema.
Visual Object (Image) Shall validate against Visual Object schema. Image Data shall conform with Visual Qualifier.
Face Time Shall validate against Time schema.
Visual Scene Geometry Shall validate against Visual Scene Geometry schema.
Produces Face Instance IDs Shall validate against Instance ID schema.
Bounding Boxes Shall validate against Bounding Box schema. Bounding Box Data shall conform with Visual Qualifier.

9 Performance Assessment

Performance Assessment of a PAF‑FIR AIM Implementation shall be performed using a dataset of faces for each face of which the Identity of the face is provided with reference to a Taxonomy.

The Performance Assessment Report of a PAF‑FIR AIM Implementation shall include:

  1. The Identifier of the PAF‑FIR AIM.
  2. The identifier of the face dataset.
  3. The identifier of the Taxonomy of face identifiers.
  4. The Performance of the PAF‑FIR AIM Implementation expressed by the Accuracy of the Identifiers provided by the output of the PAF‑FIR AIM computed on all faces of the dataset referenced in 2 using the Taxonomy referenced in 3.

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