Computer Vision Terms Glossary: Computer Vision Terms in 2024
A
Activation Function
An Activation Function is a mathematical function applied to the output of a neuron in an artificial neural network, introducing non-linearities and enabling the network to learn complex mappings.
Anomaly Detection
Anomaly Detection is the process of identifying and flagging patterns or instances that deviate significantly from the expected behavior.
Artificial Neural Networks (Anns)
Artificial Neural Networks (ANNs) are computational models inspired by the biological neural networks in the human brain, used for solving complex tasks.
B
Background Subtraction
Background Subtraction is a process in Computer Vision that involves isolating and extracting the foreground objects or regions from a video or image sequence.
Backpropagation
Backpropagation is an algorithm used in training artificial neural networks, where the gradients of the loss function with respect to the network's parameters are recursively computed and used to update the weights.
Bag-Of-Words (Bow)
Bag-of-Words (BoW) is a popular feature representation technique in natural language processing and computer vision, treating texts or images as unordered collections of features.
Biometric Identification
Biometric Identification is the process of recognizing individuals based on their unique physical or behavioral characteristics, such as fingerprints, iris patterns, or gait analysis, often used for security or access control systems.
Biometrics
Biometrics refers to the measurement and analysis of unique physical or behavioral characteristics of individuals, often used for identification purposes.
C
Camera Calibration
Camera Calibration is the process of estimating the parameters and intrinsic properties of a camera to enable accurate 3D reconstruction or measurement.
Camera Pose Estimation
Camera Pose Estimation is the task of determining the 3D position and orientation of a camera relative to the observed scene, often used in augmented reality or robotics applications.
Classification
Classification is the process of categorizing input data into predefined classes or categories based on their features or characteristics.
Computer Vision
Computer Vision is a field of study that focuses on enabling computers to understand and interpret visual information from digital images or videos.
Convolutional Neural Network
A Convolutional Neural Network (CNN) is a type of neural network designed for processing and analyzing visual data, particularly images.
Convolutional Neural Network (Cnn)
A Convolutional Neural Network (CNN) is a type of deep neural network commonly used in Computer Vision tasks, specifically designed to process grid-like data such as images.
Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are deep learning models specifically designed to process and analyze visual data, often used in computer vision tasks.
Corner Detection
Corner Detection is a process in Computer Vision that involves identifying and localizing the corners or points of interest within an image.
D
Data Annotation
Data Annotation is the process of labeling or tagging data with metadata or ground truth information for training and evaluation purposes.
Data Augmentation
Data Augmentation is a technique used to artificially increase the size or diversity of a training dataset by applying various transformations or modifications to the existing data.
Data Labeling
Data Labeling is the process of assigning annotations or labels to data, such as images or videos, to create training or validation datasets for machine learning models.
Deep Learning
Deep Learning is a subfield of Machine Learning that focuses on training artificial neural networks with multiple layers to learn and extract features from data.
Deep Neural Networks
Deep Neural Networks are complex artificial neural networks with multiple hidden layers, designed to learn and handle more complex patterns and abstractions.
Depth Estimation
Depth Estimation is the task of estimating the 3D depth information of a scene or object from a 2D image or video.
Depth Map
A Depth Map is a 2D representation of the distance or depth information of a scene, usually generated by stereo vision or depth estimation algorithms.
E
Edge Detection
Edge Detection is a process in Computer Vision that involves identifying the boundaries or edges of objects within an image.
Edge Enhancement
Edge Enhancement is a technique used to enhance the visibility and emphasis of edges within an image.
F
Facial Recognition
Facial Recognition is a technology that uses computer algorithms to identify and verify individuals based on their facial features.
Feature Descriptor
A Feature Descriptor is a compact representation of a keypoint or local feature within an image, typically used for tasks such as feature matching, image registration, or object recognition.
Feature Detection
Feature Detection is the process of identifying specific structures or patterns within an image, such as edges or corners.
Feature Extraction
Feature Extraction is the process of transforming raw data, such as images, into a representation that captures important or meaningful information.
Feature Matching
Feature Matching is a process in Computer Vision that involves comparing and matching features or keypoints between images.
Fine-Tuning
Fine-tuning is a process in Transfer Learning where a pre-trained model is further trained or adapted on a specific task or dataset.
Foreground Detection
Foreground Detection, also known as Background Subtraction, is a technique used to separate the foreground objects from the static or dynamic background in a video or image sequence.
Foreground Estimation
Foreground Estimation is the task of estimating the foreground pixels or regions within an image or video, often used for tasks such as background subtraction, object tracking, or surveillance.
Foreground Segmentation
Foreground Segmentation is the process of separating the foreground objects from the background in an image or video.
G
Generative Adversarial Network
A Generative Adversarial Network (GAN) is a type of deep learning architecture consisting of two neural networks, a generator and a discriminator, trained in an adversarial manner to generate realistic data.
Generative Adversarial Networks
Generative Adversarial Networks (GANs) are deep learning models that consist of two neural networks, a generator and a discriminator, working together to generate realistic synthetic data.
Generative Adversarial Networks (Gans)
Generative Adversarial Networks (GANs) are a class of deep learning models that consist of a generator and discriminator network to generate new data samples.
Gesture Recognition
Gesture Recognition is the process of interpreting and understanding human gestures, such as hand movements or body postures, using computer vision techniques.
H
Heatmap
A Heatmap is a visualization technique that uses color coding to represent the intensity or density of information within an image.
Histogram Equalization
Histogram Equalization is a technique used to enhance the contrast and dynamic range of an image by redistributing its pixel intensities.
Histogram Of Oriented Gradients (Hog)
Histogram of Oriented Gradients (HOG) is a feature descriptor commonly used in object detection and recognition, extracting information about local object shape and appearance.
Human Pose Estimation
Human Pose Estimation is the task of estimating the pose or body keypoint locations of a person within an image or video.
I
Image Annotation
Image Annotation refers to the process of labeling or tagging images with metadata, such as object bounding boxes, segmentation masks, or descriptive labels, to enable supervised learning or analysis.
Image Classification
Image Classification is a task in Computer Vision that involves assigning a label or category to an input image based on its content or characteristics.
Image Compression
Image Compression refers to techniques used to reduce the file size of an image while maintaining an acceptable level of visual quality.
Image Denoising
Image Denoising is the process of removing noise or undesirable artifacts from an image.
Image Enhancement
Image Enhancement refers to techniques used to improve the quality or visual appearance of an image.
Image Inpainting
Image Inpainting is the task of filling in missing or corrupted parts of an image with plausible content.
Image Morphing
Image Morphing is the process of smoothly transforming one image into another by creating a sequence of intermediate frames.
Image Processing
Image Processing refers to the techniques used to enhance, analyze, or modify images using mathematical operations.
Image Recognition
Image Recognition is the ability of a computer system to identify and classify objects or patterns within digital images.
Image Recognition System
An Image Recognition System is a computer vision system designed to recognize and identify objects, patterns, or features within images, often used for various applications such as surveillance, quality control, or autonomous navigation.
Image Reconstruction
Image Reconstruction is the process of creating a high-quality image from limited or incomplete image data, often used in medical imaging or remote sensing applications.
Image Registration
Image Registration is the process of aligning or transforming different images of the same scene to a common coordinate system.
Image Restoration
Image Restoration involves the process of improving the visual quality of a degraded or corrupted image, typically through techniques such as denoising, deblurring, or inpainting.
Image Retrieval
Image Retrieval is the task of retrieving images from a large image database that are similar or relevant to a given query image based on their visual content.
Image Segmentation
Image Segmentation is the process of partitioning an image into multiple meaningful segments or regions.
Image Segmentation Algorithms
Image Segmentation Algorithms are computational methods or techniques used to partition an image into meaningful regions or segments based on certain criteria, such as intensity, color, texture, or motion.
Image Segmentation Evaluation
Image Segmentation Evaluation involves assessing the quality and accuracy of an image segmentation algorithm by comparing the generated segmentation results with ground truth annotations or manual labels.
Image Stitching
Image Stitching is the process of combining multiple images with overlapping fields of view to create a larger composite image.
Image Super-Resolution
Image Super-Resolution is the process of generating a high-resolution image from a low-resolution input image.
Image Synthesis
Image Synthesis is the process of generating new images that are realistic or visually consistent with a given set of input images or desired properties, often used in computer graphics, virtual reality, or data augmentation for deep learning.
Image-Based Lighting
Image-Based Lighting is a technique that uses high-dynamic-range (HDR) images to accurately capture and represent the lighting information of a real-world scene, enabling realistic rendering and illumination of computer-generated objects within that scene.
Image-Based Localization
Image-Based Localization is the task of estimating the position and orientation of a camera or robot within an environment using visual information acquired from images, often used for tasks such as autonomous navigation or augmented reality.
Image-Based Modeling
Image-Based Modeling is a technique that reconstructs 3D models of objects or scenes from a set of 2D images, enabling applications such as virtual reality, augmented reality, or 3D visualization.
Image-Based Rendering
Image-Based Rendering (IBR) is a technique that generates new views of a scene or object based on a set of input images, enabling 3D reconstruction or view synthesis.
Instance Recognition
Instance Recognition is the task of recognizing and identifying instances of objects within an image, often involving identifying their location, pose, and instance-specific information.
Instance Segmentation
Instance Segmentation is a more advanced form of image segmentation that involves not only segmenting objects but also distinguishing between individual instances of the same object class.
K
Keypoint Description
Keypoint Description is the process of generating a compact and discriminative descriptor for specific keypoints within an image.
Keypoint Detection
Keypoint Detection is the process of identifying and localizing specific interest points or keypoints within an image.
L
Loss Function
A Loss Function, also known as a cost function or objective function, measures the discrepancy or error between the predicted output of a model and the true target output during training.
M
Matched Filtering
Matched Filtering is a signal processing technique used in image processing to enhance the detection of specific patterns or features in an image by filtering it with a template or matching filter.
Mean Average Precision (Map)
Mean Average Precision (mAP) is a common evaluation metric used to assess the performance of object detection and recognition algorithms.
Mean-Shift
Mean-Shift is an iterative algorithm used for finding the modes or peaks in a probability density function, often applied to image segmentation and tracking.
Model Evaluation
Model Evaluation is the process of assessing the performance or accuracy of a trained machine learning model using various metrics or evaluation criteria.
Motion Detection
Motion Detection is the process of detecting and tracking the movement of objects within a video sequence, often used for surveillance or activity recognition.
Motion Estimation
Motion Estimation is the process of estimating the motion between consecutive frames in a video sequence, which can be used for tasks such as video compression, object tracking, or video stabilization.
Motion Tracking
Motion Tracking involves analyzing image sequences to track the movement of objects or capture the motion of the camera itself.
O
Object Detection
Object Detection is a task in Computer Vision that involves identifying and localizing objects within an image or video.
Object Recognition
Object Recognition is the task of identifying and classifying specific objects or instances within an image or video.
Object Segmentation
Object Segmentation is the process of partitioning an image into distinct regions or segments, with each segment representing a separate object or region of interest.
Object Tracking
Object Tracking is the process of following and monitoring the movement of an object or person in a sequence of images or video frames.
Optical Character Recognition
Optical Character Recognition (OCR) is the technology used to extract text from images or scanned documents and convert it into editable and searchable text.
Optical Character Recognition (Ocr)
Optical Character Recognition (OCR) is the technology used to convert images of text into machine-readable text.
Optical Flow
Optical Flow is the pattern of apparent motion of objects, surfaces, and edges within a sequence of images or video frames.
Overfitting
Overfitting is a phenomenon in machine learning where a model performs well on the training data but fails to generalize and perform well on new, unseen data.
P
Pattern Recognition
Pattern Recognition is the task of identifying and classifying patterns or regularities within data, often used in computer vision for object recognition or image analysis.
Pooling
Pooling is a technique in Convolutional Neural Networks (CNNs) that reduces the spatial dimensions of feature maps, reducing the computational complexity and making the network more robust to spatial variations.
Pose Estimation
Pose Estimation is the task of estimating the pose, position, and orientation of an object or person within an image or video.
Precision
Precision is a performance metric used to measure the proportion of correctly predicted positive instances out of the total predicted positive instances.
R
Real-Time Object Detection
Real-Time Object Detection is the task of detecting and recognizing objects within a video or image stream in real-time, often used in applications such as autonomous driving, robotics, or surveillance systems.
Real-Time Tracking
Real-Time Tracking is the process of continuously and accurately tracking the movement of objects within a video sequence in real-time.
Recall
Recall is a performance metric used to measure the proportion of correctly predicted positive instances out of the total number of actual positive instances.
Recurrent Neural Networks (Rnns)
Recurrent Neural Networks (RNNs) are a type of artificial neural network designed for sequence data processing, applying the same set of weights recursively at each step.
Region Of Interest (Roi)
Region of Interest (ROI) refers to a specific area or portion within an image or video frame that is of particular interest for analysis or processing.
Robot Vision
Robot Vision is a subfield of computer vision that focuses on enabling robots to perceive, understand, and interact with their environment using visual information.
S
Saliency Detection
Saliency Detection is the process of identifying the most visually distinctive regions or objects within an image or scene.
Scale-Invariant Feature Transform (Sift)
Scale-Invariant Feature Transform (SIFT) is a popular feature detection and description technique that detects and describes local features in an image, invariant to scale and rotation.
Semantic Feature Extraction
Semantic Feature Extraction is the process of extracting high-level semantic or meaningful features from images.
Semantic Segmentation
Semantic Segmentation is the process of partitioning an image into different regions or segments based on their semantic meaning.
Semantic Understanding
Semantic Understanding involves extracting higher-level meaning or understanding from visual data, going beyond low-level feature extraction or pattern recognition.
Shadow Detection
Shadow Detection is the task of identifying and distinguishing between shadow regions and non-shadow regions within an image or video, often used for various applications such as object recognition, scene understanding, or autonomous navigation.
Spatial Filtering
Spatial Filtering is a type of image filtering performed on a pixel-by-pixel basis using a neighborhood of pixels to produce a new output image, often used for tasks such as noise reduction, edge enhancement, or feature extraction.
Speeded Up Robust Features (Surf)
Speeded Up Robust Features (SURF) is a feature detection and description technique that detects and describes local features in an image, designed to be more efficient than SIFT.
Stereo Vision
Stereo Vision is a technique that uses two or more images taken from different perspectives to estimate depth and 3D information.
Structured Light
Structured Light is a technique that projects a pattern of known geometric shapes or illumination onto a scene or object to enable accurate 3D reconstruction or depth estimation.
Super-Resolution
Super-Resolution is the process of enhancing or increasing the resolution of an image beyond its original quality.
Superpixel Segmentation
Superpixel Segmentation is a technique that groups pixels together into perceptually meaningful and coherent regions, often used as a preprocessing step for various computer vision tasks.
Supervised Learning
Supervised Learning is a type of Machine Learning where the algorithms learn patterns and relationships using labeled or annotated examples.
T
Texture Analysis
Texture Analysis is the process of characterizing and describing the texture patterns within an image.
Texture Synthesis
Texture Synthesis is the process of generating new textures that are similar to a given sample texture, often used for tasks such as texture analysis, image editing, or computer graphics.
Transfer Learning
Transfer Learning is a technique in Machine Learning where pre-trained models or knowledge from one task or domain is applied to a different but related task or domain.
U
Underfitting
Underfitting is a phenomenon in machine learning where a model is too simple or lacks the capacity to capture the underlying structure of the data, resulting in poor performance.
Unsupervised Learning
Unsupervised Learning is a type of Machine Learning where the algorithms learn patterns and relationships in data without labeled or annotated examples.
V
Video Compression
Video Compression refers to the process of reducing the size or data rate of a video while maintaining an acceptable level of visual quality, often used for efficient storage or transmission.
Video Object Detection
Video Object Detection is the task of detecting and localizing objects of interest within a video sequence, often in real-time or near-real-time scenarios.
Video Stabilization
Video Stabilization is the process of removing unwanted camera motion or shake from a video sequence, resulting in a smoother and more stable video output.
Video Summarization
Video Summarization is the process of generating a concise summary or representation of a long video sequence, often by selecting keyframes or extracting important events.
Video Surveillance
Video Surveillance is the use of video cameras to monitor and record activities in specific areas or premises.
Visual Object Tracking
Visual Object Tracking is the task of following or tracking an object of interest within a video sequence, often in the presence of occlusions, scale changes, or viewpoint variations.
Visual Odometry
Visual Odometry is the process of estimating the trajectory or motion of a camera based on the analysis of input video sequences.
Visual Saliency
Visual Saliency refers to the conspicuousness or importance of regions or objects within an image that draw the attention of human observers, often used for tasks such as image quality assessment, object recognition, or video summarization.
Visual Search
Visual Search is a process that allows users to search through large image databases using images as queries, instead of text-based search terms.