Machine Learning object detection and artificial intelligence concept. Application detect object in picture. (Blur human face)
One of the most important jobs in computer vision is image annotation. Computer vision essentially aims to give machine eyes — the capacity to perceive and comprehend the world — through various applications.
Machine learning initiatives occasionally appear to unleash futuristic technologies that we never imagined conceivable. Augmented reality, automated voice recognition, and neural machine translation are just a few of the AI-powered technologies that have the potential to alter people’s lives and enterprises all over the world.
Computer vision can also provide incredible technology (autonomous cars, facial recognition, and unmanned drones). However, without data annotation that includes image and video annotation, none of these astonishing computer vision capabilities would be conceivable.
So, this article will define the next big thing in image annotation in 2022.
What is Image Annotation?
Adding metadata to an image is known as an image annotation. Meta-data is a type of data in which multiple aspects of a picture are stated using a keyword, which is also a type of data. A car is to be labeled as a car. This data is incorporated into machine-learning algorithms.
Types of Image Annotation:
Image annotation is crucial for teaching a machine to automatically add appropriate metadata information to an image.
There are three types of image annotation methods.
1. Image Annotation Based on Retrieval:
2. Image Annotation Based on Classification
3. Image Annotation Based on Probabilistic
Returning to the original topic, what are the different forms of image annotations?
Image annotations are algorithm-based
Bounding Box Annotation
Making a rectangle drawing of lines from one corner to another of an object in an image as per its shape is known as bounding box annotation.
Polygon Annotation
Polygon annotation is one of the quickest and best ways to annotate different things for machine learning. The boundaries of an item in the frame are annotated with the highest precision in this procedure, which aids in identifying the object with the correct form and size. This sort of picture annotation technology is utilized in sports analytics to recognize various things such as street signs, logos, and face traits for broader recognition.
Cuboid Annotation
This is also known as 3D cuboid annotation, and it entails using high-quality labeling and marking the approach to highlight things in three-dimensional drawing forms. It aids in calculating the depth or distance of various items such as gadgets, buildings, and automobiles and identifies the object’s volume and space in people. Construction and building structural disciplines and radiology imaging in medical areas require 3D cuboid annotation.
Text Annotation
Giving labels to a text document is known as text annotation. Human language may be challenging to interpret, even for humans, no matter how sophisticated robots get. Specific criteria emphasize phrase components or structures in text annotation to prepare datasets for training a model that can efficiently understand human language, purpose, or emotion behind words.
Semantic Segmentation
The objective of semantic segmentation, also known as picture segmentation, is to group sections of an image that belong to the same object class. Because each pixel in an image is classified according to a category, …….
Source: https://www.datasciencecentral.com/image-annotation-overview-2022/