What is it about?

This paper introduces an innovative application called "Search by Visual Content," which uses artificial intelligence, specifically the deep learning model YOLOv8, to improve how we search for multimedia files like images and videos. Unlike traditional text-based search engines that rely on metadata, names, and types, this application allows users to search for content by inputting a similar image or video, or by specifying a certain object within the media. The tool provides fast and accurate results, making it easier to locate specific visual content amidst the vast amount of digital media available today. The application is cross-platform, meaning it works across various operating systems, and was developed using the Python programming language.

Featured Image

Why is it important?

As the volume of digital multimedia content grows rapidly, finding specific images and videos has become increasingly challenging. Traditional search engines based on text or metadata can’t effectively handle searches based on visual characteristics, leaving users frustrated. This application addresses this gap by allowing content to be searched based on its visual features, which is a significant leap forward in content retrieval. Whether you’re looking for an image with a specific object or trying to find similar visual content, this tool makes the process more intuitive and efficient. It’s particularly valuable in industries like media, e-commerce, and research, where quick and precise retrieval of visual content is essential.

Perspectives

The development of this deep learning-based content search system has the potential to revolutionize how we search for and interact with multimedia. As the application evolves, it could support even more advanced search capabilities, such as recognizing more complex visual patterns, objects, and even contexts. It could be applied in a variety of fields, from enhancing e-commerce product searches to streamlining media management for professionals in photography, film, and design. Additionally, as AI technologies continue to improve, the system’s accuracy and efficiency will only increase, making content-based searches even faster and more precise.

Leila BENAROUS
University of Laghouat

Read the Original

This page is a summary of: Deep Learning content-based search in media files, December 2024, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/acit62805.2024.10876969.
You can read the full text:

Read

Contributors

The following have contributed to this page