AI-900 Practice Question: Describe features of computer vision workloads on Azure
What is 'depth estimation' in computer vision and what are its applications?
⚠ Common exam trap
It's easy for candidates to confuse 'depth estimation' with image quality metrics (color depth or lens resolution) or with scene understanding terms like 'depth of field' or 'background embedding', rather than recognizing it as a spatial distance inference task.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Inferring the distance of objects from the camera to produce a spatial depth map
Depth estimation is a computer vision technique that infers the distance of objects from the camera, producing a spatial depth map where each pixel represents a distance value. This is commonly achieved using stereo vision (two cameras) or monocular depth estimation (single camera with deep learning models). It is a core feature of Azure Computer Vision's spatial analysis capabilities, enabling applications like augmented reality, autonomous navigation, and 3D scene reconstruction.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Measuring the depth of colour in an image (number of bits per pixel)
Why it's wrong here
Bit depth is image colour encoding — depth estimation measures spatial distance of objects from the camera.
- ✓
Inferring the distance of objects from the camera to produce a spatial depth map
Why this is correct
Depth estimation produces per-pixel distance measurements — enabling obstacle avoidance, 3D reconstruction, and AR scene understanding.
- ✗
Analysing how deeply a subject is embedded in a complex background scene
Why it's wrong here
Background complexity is an image composition concept — depth estimation measures real-world distance to objects.
- ✗
Determining how much detail is captured in a photograph based on lens quality
Why it's wrong here
Lens quality affects sharpness — depth estimation is a computer vision task for measuring object distances from imagery.
Go deeper
Related to this question
Learn chapter
Machine Learning Core Concepts
Key term
Deep learning
Deep learning is a subset of machine learning that uses multi-layered neural networks to automatically learn patterns from large amounts of data.
Key term
Feature
A feature is a distinct unit of functionality that delivers value to the user, often managed and tracked throughout the software development lifecycle.
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