Video/Image Analytics is the extraction of meaning from video and images through automated means. This can be done through the use of computer vision algorithms, natural language processing (NLP), or a combination of both. In the text analytics industry, Video/Image Analytics is used to automatically extract insights from videos or images. This might include identifying objects in an image, understanding the sentiment of an image, or extracting text from an image.
Outside of the text analytics industry, the term Video/Image Analytics might be used to refer to any number of applications that make use of computer vision or NLP to automatically understand video or images. For example, Video/Image Analytics could be used to automatically generate descriptions of photos for people with visual impairments, or to improve the accuracy of video search engines.
Video/Image Analytics is similar to terms like “computer vision” and “natural language processing.” However, the term “Video/Image Analytics” is specifically used in the text analytics industry to refer to the process of automatically extracting insights from videos or images. Other similar terms include “image recognition” and “video understanding.”
Tools used in Video/Image Analytics
Some common tools used in Video/Image Analytics include:
- Computer vision algorithms: These are algorithms that are designed to automatically interpret and understand digital images. Common computer vision tasks include object detection, facial recognition, and image classification.
- Natural language processing (NLP): This is a subfield of artificial intelligence that deals with understanding human language. NLP can be used to automatically extract meaning from text, including extracting insights from videos or images.
- Machine learning: This is a type of artificial intelligence that allows computers to learn from data, without being explicitly programmed. Machine learning is often used in conjunction with computer vision and NLP to improve the accuracy of Video/Image Analytics applications.
Video/Image Analytics and artificial intelligence
Video/Image Analytics is a subfield of artificial intelligence that deals with understanding digital video and images. Artificial intelligence is a broad field that encompasses many different subfields, including machine learning, natural language processing, and computer vision. Video/Image Analytics applications make use of one or more of these subfields to automatically understand video and images.
Applications of Video/Image Analytics
Some common applications of Video/Image Analytics include:
Facial recognition: This is the process of automatically identifying individuals in digital images or videos based on their facial features. Facial recognition systems are used for a variety of purposes, including security, law enforcement, and marketing.
Object detection: This is the process of automatically identifying objects in digital images or videos. Object detection can be used for a variety of purposes, including security and autonomous driving.
Image classification: This is the process of automatically assigning labels to digital images. Image classification can be used for a variety of purposes, including content moderation and search engine optimization.
Text extraction: This is the process of automatically extracting text from digital images. Text extraction can be used for a variety of purposes, including document processing and automatic translation.