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AI-900: Utilizing Computer Vision for Accurate Car Location and Distance Estimation

Explore the power of computer vision in determining the location of cars within an image, enabling precise distance estimation. Discover the advantages and applications of object detection in this informative guide, and learn how it can enhance your image analysis capabilities.

Question

You need to determine the location of cars in an image so that you can estimate the distance between the cars. Which type of computer vision should you use?

A. optical character recognition (OCR)
B. object detection
C. image classification
D. face detection

Answer

B. object detection

Explanation

The correct answer is B. object detection.

Object detection is a type of computer vision that can locate and label specific objects within an image, such as drawing bounding boxes around faces or cars. Object detection can be used to determine the location of cars in an image so that you can estimate the distance between the cars, as it can provide the coordinates and dimensions of the bounding boxes for each car.

Optical character recognition (OCR), image classification, and face detection are other types of computer vision, but they are not suitable for this scenario. OCR is a technique that can extract text from images, such as scanned documents, receipts, invoices, etc. Image classification is a technique that can assign a label to an entire image, such as identifying the category of an object or scene. Face detection is a technique that can locate and label human faces within an image, such as drawing bounding boxes around eyes or mouths. These techniques are useful for different applications, such as document analysis, scene recognition, or facial recognition, but they cannot determine the location of cars in an image.

Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.

The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like “indoor”, which can’t be localized with bounding boxes.

Reference

Microsoft Learn > Azure > Cognitive Services > Computer Vision > Object detection

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump