AI-900 Practice Question: Describe features of computer vision workloads on Azure
A retail store wants to analyze customer behavior in front of a specific product display. They need to determine how long each customer stands in front of the display and whether they pick up an item. Which Azure Computer Vision capability should they use?
⚠ Common exam trap
Many candidates confuse Object Detection (which only identifies objects in a static frame) with Spatial Analysis (which tracks movement and actions over time), leading them to pick Option C because they think detecting a person and an item is sufficient, but they miss the temporal and action-based requirements.
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
✓
Spatial Analysis
Spatial Analysis is the correct Azure Computer Vision capability because it is specifically designed to analyze people's movement, presence, and interactions within a physical space using video feeds. It can track how long a customer stands in front of a display (dwell time) and detect actions like picking up an item, by processing bounding boxes and skeleton data from cameras.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Image Classification
Why it's wrong here
Image Classification assigns a single categorical label to an entire image, such as 'customer_display', but it provides no bounding box and no per-object localization. It cannot track an individual's position across frames, cannot measure dwell time, and cannot infer whether a person picked up an item. Even if it correctly recognizes a scene, it lacks the temporal and spatial reasoning required to analyze customer behavior in a video stream.
- ✗
Optical Character Recognition (OCR)
Why it's wrong here
Optical Character Recognition (OCR) extracts printed or handwritten text from images using Azure's Read API, and in video it only works on static text per frame. It has no model for human bodies, body positions, or object interactions, so it cannot detect movement or a reaching/picking action. OCR answers 'what text is present?' rather than 'what is a person doing?', making it irrelevant to tracking engagement with retail displays.
- ✗
Object Detection
Why it's wrong here
Object Detection (e.g., Azure Custom Vision object detection) localizes people and items with bounding boxes within a single frame. While it can show that a person is near a display, it does not associate identities across frames, cannot calculate how long the customer stayed, and cannot reason about the sequence of actions such as reaching or picking up an item. Because the retail scenario requires continuous tracking and activity analysis, per-frame object detection alone is insufficient.
- ✓
Spatial Analysis
Why this is correct
Spatial Analysis is a computer vision capability specifically designed for analyzing people's presence, movement, and interactions within a physical space. It can measure dwell time and detect actions like a person reaching for an item, making it the correct choice for this scenario.
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