☰
Take a Quiz Test
Quiz Category
Computer Vision
Image Processing
Feature Detection
Object Detection
Object Tracking
Face Recognition
Image Classification
Semantic Segmentation
3D Computer Vision
Object Recognition in 3D
Gesture and Hand Tracking
Scene Understanding
Object Recognition in 3D Quiz Questions
1.
In object recognition, what is the primary role of "feature extraction" from 3D data?
A. Noise reduction
B. Color correction
C. Extracting distinctive features or descriptors from 3D data
D. Image resizing
view answer:
C. Extracting distinctive features or descriptors from 3D data
Explanation:
Feature extraction in object recognition involves extracting distinctive features or descriptors from 3D data for recognition tasks.
2.
What is the primary challenge in 3D object recognition when dealing with objects that have limited or no texture?
A. Image resizing
B. Color correction
C. Noise reduction
D. Feature extraction and matching on textureless surfaces
view answer:
D. Feature extraction and matching on textureless surfaces
Explanation:
Feature extraction and matching on textureless surfaces are challenges in 3D object recognition.
3.
Which 3D sensor technology is commonly used for object recognition and scene understanding, providing a detailed 3D point cloud of the environment?
A. LiDAR
B. Histogram equalization
C. Median filtering
D. Sobel operator
view answer:
A. LiDAR
Explanation:
LiDAR (Light Detection and Ranging) is commonly used for object recognition, providing a detailed 3D point cloud of the environment.
4.
In 3D object recognition, what does "pose estimation" refer to?
A. Noise reduction
B. Color correction
C. Determining the position and orientation of an object in 3D space
D. Image resizing
view answer:
C. Determining the position and orientation of an object in 3D space
Explanation:
Pose estimation in 3D object recognition involves determining the position and orientation of an object in 3D space.
5.
What is the primary advantage of using "multi-view stereo" (MVS) techniques in 3D object recognition?
A. Improved image resizing capabilities
B. Noise reduction
C. Reconstructing detailed 3D object models from multiple viewpoints
D. Precise color correction
view answer:
C. Reconstructing detailed 3D object models from multiple viewpoints
Explanation:
Multi-view stereo (MVS) techniques reconstruct detailed 3D object models from multiple viewpoints in 3D object recognition.
6.
In 3D object recognition, what is the primary role of "3D object tracking"?
A. Noise reduction
B. Color correction
C. Monitoring and tracking the 3D motion of objects in the scene
D. Image resizing
view answer:
C. Monitoring and tracking the 3D motion of objects in the scene
Explanation:
3D object tracking involves monitoring and tracking the 3D motion of objects in the scene for recognition.
7.
What is the primary purpose of "3D shape descriptors" in 3D object recognition?
A. Image resizing
B. Color correction
C. Noise reduction
D. Representing the 3D shape of objects with compact and discriminative descriptors
view answer:
D. Representing the 3D shape of objects with compact and discriminative descriptors
Explanation:
3D shape descriptors in 3D object recognition are used to represent the 3D shape of objects with compact and discriminative descriptors.
8.
Which 3D computer vision technique is used for creating a 3D model of an object by capturing depth data from different viewpoints?
A. Stereo vision
B. 3D object reconstruction
C. Median filtering
D. Histogram equalization
view answer:
B. 3D object reconstruction
Explanation:
3D object reconstruction creates a 3D model by capturing depth data from different viewpoints in 3D object recognition.
9.
In 3D object recognition, what is the primary challenge when dealing with partial object views or occlusions?
A. Image resizing
B. Color correction
C. Noise reduction
D. Handling partial object recognition and occlusion handling
view answer:
D. Handling partial object recognition and occlusion handling
Explanation:
Handling partial object recognition and occlusion is a challenge in 3D object recognition.
10.
What is the primary advantage of using "deep learning" in 3D object recognition?
A. Improved image resizing capabilities
B. Noise reduction
C. The ability to learn complex features from 3D data
D. Precise color correction
view answer:
C. The ability to learn complex features from 3D data
Explanation:
Deep learning in 3D object recognition allows the learning of complex features from 3D data.
11.
Which 3D object recognition technique is focused on classifying objects into categories based on their 3D shapes?
A. 3D shape classification
B. Color correction
C. Noise reduction
D. Image resizing
view answer:
A. 3D shape classification
Explanation:
3D shape classification in 3D object recognition classifies objects into categories based on their 3D shapes.
12.
What is the primary goal of "3D object instance recognition" in 3D computer vision?
A. Noise reduction
B. Color correction
C. Distinguishing and recognizing individual instances of objects in the scene
D. Image resizing
view answer:
C. Distinguishing and recognizing individual instances of objects in the scene
Explanation:
3D object instance recognition aims to distinguish and recognize individual instances of objects in the scene.
13.
In 3D object recognition, what is the primary challenge when dealing with variations in object scale and pose?
A. Image resizing
B. Color correction
C. Noise reduction
D. Handling scale and pose invariance
view answer:
D. Handling scale and pose invariance
Explanation:
Handling scale and pose invariance is a challenge in 3D object recognition.
14.
What is the primary purpose of "local feature matching" in 3D object recognition?
A. Noise reduction
B. Color correction
C. Matching local features between the 3D model and observed scene
D. Image resizing
view answer:
C. Matching local features between the 3D model and observed scene
Explanation:
Local feature matching in 3D object recognition involves matching local features between the 3D model and the observed scene.
15.
In 3D object recognition, what is the primary advantage of using "point cloud data" for representation?
A. Improved image resizing capabilities
B. Noise reduction
C. Capturing fine-grained object details
D. Precise color correction
view answer:
B. Noise reduction
Explanation:
Point cloud data is suitable for noise reduction and capturing fine-grained object details in 3D object recognition.
16.
Which 3D sensor technology is commonly used in handheld devices for object recognition and augmented reality applications?
A. Time-of-flight sensor
B. Histogram equalization
C. Median filtering
D. Sobel operator
view answer:
A. Time-of-flight sensor
Explanation:
Time-of-flight sensors are commonly used in handheld devices for object recognition and augmented reality applications.
17.
In 3D object recognition, what is the primary role of "3D feature detection"?
A. Noise reduction
B. Color correction
C. Detecting distinctive features in the 3D scene
D. Image resizing
view answer:
C. Detecting distinctive features in the 3D scene
Explanation:
3D feature detection in 3D object recognition involves detecting distinctive features in the 3D scene.
18.
What is the primary challenge in 3D object recognition when dealing with objects in cluttered scenes?
A. Image resizing
B. Color correction
C. Noise reduction
D. Object segmentation and recognition in cluttered environments
view answer:
D. Object segmentation and recognition in cluttered environments
Explanation:
Object segmentation and recognition in cluttered environments are challenges in 3D object recognition.
19.
Which 3D computer vision technique is used for recognizing objects based on their 3D shapes while ignoring color and texture information?
A. Shape-based recognition
B. Color correction
C. Noise reduction
D. Image resizing
view answer:
A. Shape-based recognition
Explanation:
Shape-based recognition in 3D object recognition focuses on recognizing objects based on their 3D shapes without considering color and texture.
20.
What is the primary advantage of "object category recognition" in 3D object recognition?
A. Improved image resizing capabilities
B. Noise reduction
C. Classifying objects into predefined categories
D. Precise color correction
view answer:
C. Classifying objects into predefined categories
Explanation:
Object category recognition classifies objects into predefined categories in 3D object recognition.
21.
In 3D object recognition, what is the primary challenge when dealing with objects under varying lighting conditions?
A. Image resizing
B. Color correction
C. Noise reduction
D. Handling illumination changes and achieving robust recognition
view answer:
D. Handling illumination changes and achieving robust recognition
Explanation:
Handling illumination changes and achieving robust recognition is a challenge in 3D object recognition.
22.
Which 3D computer vision technique is used to capture the 3D shape of an object by projecting a structured light pattern onto it?
A. Structured light scanning
B. Histogram equalization
C. Median filtering
D. Sobel operator
view answer:
A. Structured light scanning
Explanation:
Structured light scanning captures the 3D shape of an object by projecting a structured light pattern onto it in 3D object recognition.
23.
In 3D object recognition, what is the primary goal of "partial matching"?
A. Noise reduction
B. Color correction
C. Matching partially observed 3D objects to complete models
D. Image resizing
view answer:
C. Matching partially observed 3D objects to complete models
Explanation:
Partial matching in 3D object recognition involves matching partially observed 3D objects to complete models.
24.
What is the primary purpose of "3D object localization" in 3D computer vision?
A. Noise reduction
B. Color correction
C. Determining the 3D position of an object in the scene
D. Image resizing
view answer:
C. Determining the 3D position of an object in the scene
Explanation:
3D object localization determines the 3D position of an object in the scene in 3D computer vision.
25.
In 3D object recognition, what is the primary challenge when dealing with objects that have complex geometric shapes?
A. Image resizing
B. Color correction
C. Noise reduction
D. Extracting meaningful features from complex shapes
view answer:
D. Extracting meaningful features from complex shapes
Explanation:
Extracting meaningful features from complex shapes is a challenge in 3D object recognition.
26.
Which 3D computer vision technique is used for recognizing objects based on their 3D point cloud representations?
A. Point cloud recognition
B. Histogram equalization
C. Median filtering
D. Sobel operator
view answer:
A. Point cloud recognition
Explanation:
Point cloud recognition recognizes objects based on their 3D point cloud representations in 3D object recognition.
27.
What is the primary advantage of using "template matching" in 3D object recognition?
A. Improved image resizing capabilities
B. Noise reduction
C. The ability to recognize objects based on predefined templates
D. Precise color correction
view answer:
C. The ability to recognize objects based on predefined templates
Explanation:
Template matching in 3D object recognition recognizes objects based on predefined templates.
28.
In 3D object recognition, what is the primary role of "3D object segmentation"?
A. Noise reduction
B. Color correction
C. Identifying and separating objects in the 3D scene
D. Image resizing
view answer:
C. Identifying and separating objects in the 3D scene
Explanation:
3D object segmentation identifies and separates objects in the 3D scene for recognition purposes.
29.
What is the primary goal of object recognition in 3D computer vision?
A. Noise reduction
B. Image resizing
C. Identifying and classifying objects in three-dimensional space
D. Color correction
view answer:
C. Identifying and classifying objects in three-dimensional space
Explanation:
Object recognition in 3D computer vision focuses on identifying and classifying objects in three-dimensional space.
30.
Which technique in object recognition is commonly used to match a 3D model of an object to the observed 3D scene data?
A. Histogram equalization
B. 3D model registration
C. Median filtering
D. Sobel operator
view answer:
B. 3D model registration
Explanation:
3D model registration is used to match a 3D model of an object to the observed 3D scene data in object recognition.
© aionlinecourse.com All rights reserved.