Real-time object detection and augmentation
Year: 2024
Type: article
Abstract: This study presents the development of a real-time object detection and augmentation system using TensorFlow and Unity it leverages TensorFlow model to identify and classify objects in real-time from a camera feed, and Unity to integrate and display corresponding 3D virtual objects in an augmented reality environment. By creating a mapping system to pair detected objects with their virtual counterparts, the system aims to enhance user interaction through dynamic and immersive AR experiences. The study addresses the challenges of real-time processing and seamless integration, demonstrating the potential of combining machine learning and augmented reality to enrich interactive applications across various domains.
Authors: Saikumar P, Divya TL
Institution: R.V. College of Engineering
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4402139702