Data generation system

Abstract

The invention discloses a data generation system. The data generation system comprises a terminal, a server and a database, the data generation system organizes three-dimensional scene data, analog data and structured data based on an entity component system architecture; wherein three-dimensional scene data based on entity and component organization is stored in the database; the terminal collects a user-defined three-dimensional scene condition through a three-dimensional scene editing interface, collects a processing instruction edited by a user through a processing instruction editing interface provided based on the system, and sends the three-dimensional scene condition and the processing instruction to the server; and the server generates a three-dimensional scene graph meeting three-dimensional scene conditions according to the three-dimensional scene data, then adjusts the three-dimensional scene graph according to the processing instruction, and performs sensor data simulationbased on the three-dimensional scene graph according to the processing instruction to generate simulation data or / and directly outputs and stores structured data. The data generation system can generate a large amount of three-dimensional data with high quality and accurate annotation, and is low in cost.

Description

technical field [0001] The invention belongs to the fields of computer graphics, computer vision and simulation, and in particular relates to a data generation system. Background technique [0002] AI is the most powerful technological force of our time. The first phase of artificial intelligence will enable a new level of software automation, thereby helping many industries to improve productivity; later, artificial intelligence combined with sensors and actuators will become the core of a new generation of autonomous machines. [0003] In the fields of artificial intelligence, autonomous driving, robotics, etc., the final quality of the product depends on the quality and scale of the training data. Therefore, both industry and academia have great demand for high-quality data in their respective fields. In recent years, in the booming field of unmanned autonomous driving, the industry has been using a large number of synthetic simulation data for training. Extensive use ...

AI Technical Summary

Problems solved by technology

[0006] Disadvantage 1: High cost of data acquisition and simulation

Affected by factors such as the cost of specific acquisition equipment, policy and legal supervision, and labor costs, the cost of acquiring real 3D data is expensive. In order to solve the problem of high cost of acquiring real 3D data, a simulation system can be built to synthesize virtual 3D data using the simulation system. However, the simulation system The construction of the still requires a lot of cost

[0007] Disadvantage 2: low data quality

Affected by differences in acquisition equipment, acquisition environment, and acquisition operation process, the real 3D data collected is very different and irregular, and the data set specifications of different companies in different periods may also be different, resulting in the formation of isolated data islands and difficulty in integration very big

[0008] Disadvantage 3: High cost of data labeling and low labeling accuracy

Both real 3D data and virtual 3D data require a lot of manpower to label semantic information, so the cost of data labeling is high; due to low data quality and high professional depth, the accuracy of manual labeling is difficult to guarantee

[0009] Disadvantage 4: limited data production capacity

At present, 3D data is still collected and analyzed in a real physical environment. Due to the limitations of collection equipment and physical principles, a large number of phenomena and scenes cannot be collected by existing collection equipment.

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