Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Mawqifka Aadanaha

Dib-u-eegis 2D waxay soo bandhigaan qodobbada muhiimka ah, dhuumaha kor-hoos u socda iyo kuwa hoose, Qaybaha Affinity Fields iyo waxa qiyaasaha sawirka-diyaaradu aanay dhisi karin.

Wadooyinka haga ee la xidhiidhaQiyaasta Mawqifka Aadanaha
Su'aal 1 ee 8

Maxay tahay qiyaasta mawqifka bini'aadamka ee ugu horrayn lagu ogaado?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Maxay tahay qiyaasta mawqifka bini'aadamka ee ugu horrayn lagu ogaado?
    • Jagooyinka kala-goysyada jidhka ama qodobbada muhiimka ah
    • Midabada dharka
    • Magaca qofka
    • Cabbirka faylka sawirka
  2. Sidee u shaqeeyaan hababka qiimaynta ee kor-ka-sare?
    • Dhammaan kala goysyada hal mar ayay ogaadaan, ka dibna kooxeeyaan
    • Marka hore waxay ogaadaan qof kasta, ka dibna waxay ka helaan xubnaha gudaha sanduuqa
    • Weligood ma isticmaalaan sanduuqyada wax lagu xidho
    • Kaliya waxay ka shaqeeyaan hal goys oo taagan
  3. What does OpenPose predict to estimate body-part locations?
    • A direct 3D skeleton with depth
    • A single bounding box per frame
    • Confidence maps for candidate body-part locations
    • A sequence of spoken joint names
  4. What step does the OpenPose parser use to associate candidate body parts into full poses?
    • A face-recognition classifier
    • A top-down detector for every limb
    • A language-model prompt
    • A set of bipartite matchings scored with Part Affinity Fields
  5. What failure mode of top-down pose estimation does the OpenPose paper discuss in crowded scenes?
    • A person detector may miss people close together, and the pose stage cannot recover them
    • It always detects more people than are present
    • It cannot estimate any 2D keypoints
    • It requires a 3D depth camera
  6. Which additional keypoint groups did the OpenPose paper include in its system?
    • Only facial landmarks
    • Body, foot, hand and facial keypoints
    • A 3D skeleton with medical diagnoses
    • Only fingertip positions
  7. What information do Part Affinity Fields encode to connect keypoints?
    • A person’s identity from face recognition
    • Depth in meters for every body joint
    • Vectors indicating limb position and orientation across the image
    • The camera exposure settings
  8. What can a 2D pose model conclude directly from image keypoints?
    • A person’s medical diagnosis
    • Exact real-world joint depth without additional information
    • The person’s intentions
    • Approximate joint locations in image coordinates