Practice AR development vocabulary: marker-based vs. markerless AR, image tracking, plane detection, AR anchors, world-locked vs. screen-locked content, and ARKit/ARCore concepts.
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What is 'marker-based AR' and how does it differ from markerless AR?
Marker-based AR is reliable and precise — you scan a specific image and virtual content appears on it. Markerless AR (used in ARKit/ARCore) detects environmental features — floors, tables, walls — to place content without pre-prepared targets, enabling more flexible experiences.
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What is 'plane detection' in ARKit and ARCore?
Plane detection is one of the foundational ARKit/ARCore features: the device's sensor data and computer vision identify flat surfaces in the environment. This lets developers anchor virtual furniture on a real floor or stick notes to a real wall.
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What is an 'AR anchor' and what problem does it solve?
An AR anchor is a fixed point in real-world space tracked by the AR framework. Attaching virtual content to an anchor ensures it stays in the same physical location as the user moves — without anchors, virtual objects would drift as tracking error accumulates.
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What is 'world-locked' content in AR?
World-locked content is anchored to real-world coordinates: a virtual chair stays on the real floor as you walk around it. This contrasts with screen-locked content (which moves with the screen like a HUD) or body-locked content (which follows the user).
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An AR developer says 'the AR anchor persists across sessions.' What does this mean?
Persistent anchors survive app restarts: the framework relocates the saved anchor relative to the real environment when the user returns. This enables use cases like virtual notes stuck to a real wall that reappear the next day.
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Sarah from the AR team sent this Slack message: 'Just spent an hour debugging why our virtual furniture wasn't snapping onto the floor correctly. Turns out we weren't using plane detection properly – it was detecting a wall instead of the table!'. What is 'plane detection' in ARKit or ARCore referring to?
Plane detection is a core AR technology that enables the system to understand the physical world around it. Specifically, it's about accurately identifying and measuring surfaces like floors and tables – this information is then used to correctly position virtual objects within the scene. Incorrect options focus on broader AR concepts or individual object manipulation.
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David is writing a pull request description for an AR feature that uses 'world-locked' content. He writes: 'This allows the virtual dinosaur to stay exactly where it was placed in the user's room, regardless of movement.' What does 'world-locked' content primarily achieve in AR development?
'World-locked' content is a key concept in AR where virtual objects are anchored to specific locations within the real world. This means they remain fixed relative to those locations, regardless of the user's movement – it's about spatial stability. Option A describes tracking; option C relates to lighting; and option D refers to session persistence.
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Alex: 'I'm seeing intermittent issues with the AR object placement. Sometimes it's fine, sometimes the virtual car appears partially inside a wall! I've checked my code thoroughly.' What is the most likely underlying cause Alex should investigate related to AR development?
Intermittent placement issues suggest a problem with the core AR tracking. While lighting and reflections can cause problems, corrupted camera calibration data is the most probable explanation for inconsistent object positioning within a scene – this directly affects plane detection and anchor stability. The user's environment likely isn't the root cause of the intermittent behavior.
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PR Description: 'Implemented world-locked content to ensure the virtual sculpture remains fixed in place during user movement. Utilized ARKit's `ARAnchorNode` and its associated tracking capabilities for accurate placement.' What is the primary benefit of using ARAnchorNode as described here?
The core function of ARAnchorNode is to establish a stable anchor point in the physical world. This allows virtual objects to maintain their position relative to that anchor, preventing them from drifting or moving with user movement – this is what 'world-locked' content achieves. The other options describe different aspects of ARKit functionality (orientation tracking, network communication, and rendering).
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Ben from the AR team just posted this comment on your code review: 'The ARAnchorNode isn't updating its position correctly. It seems to be stuck at the initial placement even after the user moves around.' What is the most likely issue causing this problem?
Ben's comment points to a core problem with AR anchoring – the node isn't reacting to changes in its environment. Option A is possible but less likely than a bug within ARKit itself, which manages the anchor updates. Options C and D are unrelated to the scenario described.
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Maria is explaining the concept of 'markerless AR' to a new team member. She says: 'It allows us to place virtual objects in any space without needing a specific image or pattern. Instead, it uses sophisticated algorithms to understand the surrounding environment.' Which technology primarily enables this functionality?
Maria is describing markerless AR, which relies on the device's camera to understand its surroundings. 'Plane detection' – using computer vision to identify surfaces like floors and tables – is the key technology that allows virtual objects to be placed in these spaces without needing pre-defined markers. GPS and QR codes are not relevant for this approach.
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You're reviewing a pull request that implements 'world-locked' content in an AR app. The PR description states: 'This feature ensures the virtual object remains fixed to a specific point in the user's environment, regardless of their movement.' What is the primary benefit of using world-locked content in this scenario?
World-locked content is essential for creating realistic AR experiences where virtual objects should stay in a fixed location relative to the user's environment. This enables more complex interactions (e.g., placing furniture) and prevents the object from drifting due to tracking inaccuracies – option A & B are side effects, not benefits.
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David reports: 'I'm getting sporadic placement errors with our AR objects. Sometimes they appear correctly, but other times they get stuck inside walls or floors.' Considering the concept of 'AR anchors', what is the MOST likely reason for this inconsistent behavior?
David's issue suggests problems with AR anchor stability. Inaccurate plane detection (the core of anchoring) can cause the virtual object to be placed incorrectly when the device's environment map is temporarily flawed. While GPS and movement speed could contribute, inaccurate plane detection is the most direct explanation.
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During a standup meeting, Emily says: 'We're using ARKit's `ARAnchorNode` to place our virtual assets. We've enabled 'persistence' for these anchors, which means they should remain valid even after the user closes and reopens the app.' What does 'persistence' of an AR anchor primarily achieve?
'Persistence' in AR anchors means the anchor retains its validity even after the app is closed and reopened. This is crucial for maintaining object placement across sessions – without persistence, the anchor would be reset each time.
What does this Wearables & Spatial Computing Language exercise cover?
This exercise, "AR Development Vocabulary Quiz", tests your understanding of wearables & spatial computing language vocabulary and phrasing through 14 multiple-choice questions drawn from real workplace scenarios.
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