The AI solution is evaluating specific attributes and quality metrics of the face (exposure, noise, occlusion), not simply locating it or identifying the person.

• Facial detection is the process of locating a face in an image, typically by providing bounding box coordinates.
• Facial recognition is the process of identifying or verifying a specific individual.
• Facial analysis (or face attribute analysis) is the process of extracting characteristics from a detected face. The scenario's requirements—evaluating exposure, noise, and occlusion—are explicit examples of face attribute analysis.

Microsoft Azure AI Vision Documentation (Official Vendor Documentation)

Reference: "Face detection and attributes." Azure AI Vision documentation.

Citation: In the "Face attributes" section, the service description explicitly lists the attributes that can be returned from analysis. This includes "Occlusion... Exposure... Noise." This confirms that analyzing these specific photographic qualities is a function of face attribute analysis, which is distinct from mere detection or recognition.

ACM Computing Surveys (Peer-Reviewed Academic Publication)

Reference: Han, H., Wang, Z., Zhang, Z., & Shan, S. (2020). "A Survey on Face Attributes Analysis." ACM Computing Surveys, 53(2), Article 40, pp. 1–36.

Citation (DOI): https://doi.org/10.1145/3371909

Justification: This survey paper defines "Face Attributes Analysis" (FAA) as the task of "predicting a set of attributes (e.g., gender, age, expression, or... 'low quality' attributes) given a facial image." The task described in the question (evaluating noise, exposure) falls directly under this academic definition.

IEEE Transactions on Pattern Analysis and Machine Intelligence (Peer-Reviewed Academic Publication)

Reference: Kumar, N., Belhumeur, P. N., & Nayar, S. K. (2009). "FaceTracer: A Search Engine for Large Collections of Images with Faces." IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(5), 827–840.

Citation (DOI): https://doi.org/10.1109/TPAMI.2009.48

Justification: This foundational paper discusses descriptors for faces, distinguishing between "detection" (finding the face) and "analysis" of attributes, such as pose, illumination (exposure), and occlusion, which are used to describe the state of the face in the image rather than the identity of the person.