Pose Estimation MCQs With Answers

Computer MCQs 360May 11, 2024

0 7 1 minute read

Welcome to the Pose Estimation MCQs with Answers. In this post, we have shared Pose Estimation Online Test for different competitive exams. Find practice Pose Estimation Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Pose Estimation.

Pose Estimation Online Quiz

By presenting 3 options to choose from, Pose Estimation Quiz which cover a wide range of topics and levels of difficulty, making them adaptable to various learning objectives and preferences. You will have to read all the given answers of Pose Estimation Questions and Answers and click over the correct answer.

Test Name: Pose Estimation MCQ Quiz Practice
Type: Quiz Test
Total Questions: 40
Total Marks: 40
Time: 40 minutes

Note: Answer of the questions will change randomly each time you start the test. Practice each quiz test at least 3 times if you want to secure High Marks. Once you are finished, click the View Results button. If any answer looks wrong to you in Quizzes. simply click on question and comment below that question. so that we can update the answer in the quiz section.

Pose Estimation

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1 / 40

Which technique estimates pose from a sequence of video frames?

Static Pose Estimation

Temporal Pose Estimation (correct)

Spatial Pose Estimation

2 / 40

Which application area uses pose estimation for behavior analysis and surveillance?

Security and surveillance (correct)

3D modeling

Virtual reality (VR)

3 / 40

What does SPPE stand for in the context of pose estimation networks?

Sequential Pose Prediction

Spatial Pose Processing

Single-Stage Pose Estimation (correct)

4 / 40

Which deep learning architecture is often used for pose estimation tasks?

Recurrent Neural Networks (RNNs)

Convolutional Neural Networks (CNNs) (correct)

Generative Adversarial Networks (GANs)

5 / 40

Which technique estimates human poses using deep neural networks and heatmaps?

GANs

VAEs (Variational Autoencoders)

PoseNet (correct)

6 / 40

What does MPJPE stand for in the context of pose estimation evaluation metrics?

Maximum Per Joint Position Error

Median Per Joint Position Error

Mean Per Joint Position Error (correct)

7 / 40

Which technique estimates poses from RGB images without depth information?

3D pose estimation

Multi-view pose estimation

2D pose estimation (correct)

8 / 40

What is the primary advantage of using Kalman filters in pose estimation?

Real-time computation

Depth sensing

Smoothing noisy pose estimates (correct)

9 / 40

What does HOG feature extraction focus on in the context of pose estimation preprocessing?

Edge and gradient orientation (correct)

Color intensity

Texture analysis

10 / 40

Which technique combines pose estimation with facial recognition for identity verification?

Face Pose Recognition (correct)

Emotion Detection

Gesture Recognition

11 / 40

Which technique estimates 3D poses from 2D images without explicit depth information?

Monocular depth estimation (correct)

Perspective correction

Triangulation

12 / 40

What does LCR-Net++ focus on in the context of pose estimation?

Large-scale Crowd Pose Estimation (correct)

Low-contrast Ratio

Localized Calibration

13 / 40

Which technique estimates pose by analyzing skeletal structures in images?

Object tracking

Skeletal Pose Estimation (correct)

Facial recognition

14 / 40

Which technique estimates 3D poses using multi-camera setups?

Depth sensing

Time-of-Flight (ToF)

Multi-view stereo (correct)

15 / 40

What does LCR-Net++ focus on in the context of pose estimation?

Low-level Contrast Ratio

Localized Calibration

Large-scale Crowd Pose Estimation (correct)

16 / 40

What does MTCNN stand for in the context of pose estimation from images?

Multi-task Cascaded Convolutional Networks (correct)

Multi-layer Transformer Convolutional Networks

Multi-view Temporal Convolutional Networks

17 / 40

What does RGB-D stand for in the context of pose estimation?

Remote Global Depth

Reflective Gradient Depth

Red-Green-Blue Depth (correct)

18 / 40

Which neural network architecture is commonly used for real-time pose estimation on mobile devices?

ResNet

MobileNet (correct)

Inception

19 / 40

What is the primary use of pose estimation in autonomous robotics?

Navigation and interaction (correct)

Data compression

Image enhancement

20 / 40

What does HPE stand for in the context of pose estimation?

Human Pose Estimation (correct)

High-Performance Evaluation

Hierarchical Pose Estimation

21 / 40

What is pose estimation in computer vision?

Classifying objects

Estimating the position and orientation of objects (correct)

Detecting object boundaries

22 / 40

What is the primary challenge in human pose estimation?

Lighting and shadows

Articulation and occlusion (correct)

Texture and color

23 / 40

Which approach combines pose estimation with gesture recognition?

Speech synthesis

Facial expression analysis

Pose Gesture Recognition (correct)

24 / 40

What does APE stand for in the context of pose estimation metrics?

Average Pose Error (correct)

Adaptive Pose Estimation

Angle Pose Evaluation

25 / 40

Which technique is commonly used for pose estimation using single cameras?

Optical flow

Histogram of Oriented Gradients (HOG)

Perspective-n-Point (PnP) (correct)

26 / 40

Which dataset is commonly used for benchmarking pose estimation algorithms?

ImageNet

COCO (Common Objects in Context)

MPII Human Pose (correct)

27 / 40

Which sensor is commonly used for depth-based pose estimation?

LiDAR

Radar

Kinect (correct)

28 / 40

Which application area benefits from pose estimation technology?

Augmented reality (AR) (correct)

Speech recognition

Optical character recognition

29 / 40

What does COCO keypoints refer to in the context of pose estimation datasets?

Common Objects in Context keypoints (correct)

COmprehensive COntext

COlor COmputation

30 / 40

What is the primary challenge of pose estimation in crowded scenes?

Occlusion and overlapping poses (correct)

Background clutter

Lighting variation

31 / 40

What is the primary advantage of using synthetic data for training pose estimation models?

Data diversity and scalability (correct)

Reduced computational cost

Real-world variability

32 / 40

What is the primary benefit of using ensemble methods in pose estimation models?

Lower memory usage

Real-time performance

Improved robustness and generalization (correct)

33 / 40

Which mathematical technique is often used for 3D pose estimation from 2D images?

Affine transformation

Perspective projection (correct)

Principal component analysis

34 / 40

What is the advantage of using multi-view pose estimation over single-view?

Improved accuracy (correct)

Lower memory usage

Faster computation

35 / 40

What is the primary role of pose estimation in sports analytics?

Ticket sales optimization

Player recruitment

Performance analysis and training (correct)

36 / 40

Which approach combines pose estimation with semantic segmentation for understanding human actions?

Object Detection

Pose-based Action Recognition (correct)

Face Recognition

37 / 40

Which deep learning framework is commonly used for developing pose estimation models?

PyTorch

TensorFlow (correct)

Keras

38 / 40

Which evaluation metric measures the accuracy of pose estimation by comparing joint positions?

F1-score

IoU (Intersection over Union)

PCK (Percentage of Correct Keypoints) (correct)

39 / 40

Which algorithm estimates human poses using body joint keypoints?

Mask R-CNN

YOLO (You Only Look Once)

OpenPose (correct)

40 / 40

What is the primary advantage of using transfer learning in pose estimation?

Improved performance with less data (correct)

Higher computational cost

Real-time processing

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Computer MCQs 360May 11, 2024

0 7 1 minute read