The Object Tracking Pipeline enables the real-time tracking of moving objects using artificial intelligence and deep learning-based algorithms. This system can adapt different tracking algorithms to various scenarios.
The object detection pipeline allows for the creation of high-quality training data for AI models using 3D assets and synthetic data. Omniverse Replicator offers customizable sensors, batch rendering, and domain randomization features for use in different sectors (retail, manufacturing, autonomous vehicles, smart cities, factories). This enhances the model's ability to generalize across various scenarios.
The Omniverse Platform supports the process with connect, simulation, RTX rendering, and data management capabilities. All these operations can be carried out in the cloud, data centers, or on workstations. This pipeline offers an integrated workflow encompassing visualization, annotation, randomization, and output generation stages.
More powerful AI models are created by using real and synthetic data together.
Model performance continuously improves through the simulation of different scenarios.
Labeling, data generation, and processing procedures are fully automated.
Adaptable to different needs with various tracking algorithms.
Provides stable tracking even in fast and dense environments.
Can track more than one object simultaneously.
Offers the ability to make rapid decisions with instant data.
