Real-Time 3D Visualization For Deep Learning In Automotive

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Real-Time 3D Visualization For Deep Learning In Automotive

Deep Learning In Autonomous Vehicles / ADAS

Autonomous vehicle operation:

  1. Perception
  2. Localization
  3. Path Planning
  4. Control

Computer vision (Perception) learning requires a lot of visual data, which can be easily generated by real-time 3D engine software
from virtual scenarios.

Virtual scenarios can be used for pre-validation of autonomous systems behavior (Control) as well (virtual test driving).

Requirements for virtual 3D environments:

  • Photorealistic image quality
  • Physically-correct lighting
  • Multiple wide-angle surrounding cameras
  • Sensor simulation (LIDAR, radar, sonar…)
  • Access to semantic data of objects (labels)
  • Procedural scene configuration (vehicle/pedestrian positions, obstacles, lighting, weather conditions)

Compared to conventional approaches (manual dataset gathering and labeling, vehicle testing tracks), using a 3D engine requires less time, effort, and resources.

Real-Time 3D Visualization Software Development Kit

Photorealistic Visuals

  • Physically-based rendering
  • Energy conservation model
  • Dynamic lights, shadows, and reflections
  • GGX BRDF: realistic speck from light sources
  • Fresnel reflections, reflections on rough surfaces
  • Screen Space Ray Tracing Reflections (SSRR)
  • Configurable anti-aliasing algorithms
  • Unique Screen-Space Ray Tracing Global Illumination (SSRTGI) technology

Physically-correct visualization of the learning dataset = reliable computer vision for real roads.

Photorealistic Visuals
Photorealistic Visuals

Virtual Cameras & Sensor Fusion

Surround Cameras

Multiple surround cameras can be implemented with linear or fisheye (panoramic) views. Monocular / stereo dash cam setups for ADAS are also easily configurable.

LiDAR

Lidar

360° scanning laser sensor is supported. Distances to the surrounding objects can be fed into AI algorithms in real-time, regardless of lighting conditions.

Radar

Sensors

Short-wave radars can be imitated with fast access to the scene depth data. The same precise data can be used for short-range sonar imitation.

Special-Purpose Sensors

Sensors

UNIGINE 2 Sim can be used to imitate other types of special sensors, e.g. thermal, night vision, and infrared ones.

Georeferenced Scenes

UNIGINE 2 Sim SDK is built for the correct virtual representation of the real world, at scale.

  • Increased object positioning precision: 64-bit precision per coordinate
  • Support for 3D ellipsoid Earth model (WGS84, other coordinates systems)
  • Support for geodata formats (elevation / imagery / vector)
  • Ephemeris system for celestial bodies positions depending on time/coordinates
  • The performance-optimized object cluster system
Georeferenced Scenes
Georeferenced Scenes

Automatic Data Annotation

UNIGINE 2 Sim scenes already contain the classification information for each frame, making them an auto-labeled ML dataset. Ground truth data can be easily accessed for each pixel. Unlike manual tagging, there is a 0% classification error.

  • Per-object property system for semantic data
  • Easy object masking
  • Extensive access to the scene graph
  • Fast object visibility checks
  • Efficient occlusion control
  • 24-bit material masks
  • Object bounds info for segmentation
  • evaluation

Easy Scenario Reconfiguration

You can get an unlimited number of scenarios by changing any of these variable parameters, which are dynamically controlled via API:

  • Autonomous vehicle position
  • Surrounding traffic
  • Pedestrians
  • Obstacles
  • Accidents
  • Road condition
  • Lighting conditions
  • Weather conditions

The increased number of situations and test cases explored in this way should improve system reliability dramatically.

  • Reconfiguration
  • Reconfiguration
  • Reconfiguration

High Performance

UNIGINE 2 Sim was designed to handle large, complex procedural scenes, filled with dynamic entities.

The 3D engine demonstrates high and stable performance even working on consumer-grade hardware. This proves useful and time-saving when it comes to iterative AI training.

There is the multi-years close cooperation of UNIGINE with leading hardware vendors (AMD, Intel, NVIDIA) on performance optimization.

Vehicle Dynamics Simulation

UNIGINE 2 Sim SDK includes a generic vehicle dynamics system, which can be fine for background traffic or prototype applications (before you bring
more sophisticated software algorithms or hardware-in-the-loop simulation in).

  • Main vehicle systems: engine, gearbox, transfer case, axles, differential, wheels, suspension, steering, brakes
  • Configurable drivetrain: FWD, RWD, 4WD, multi-axle vehicles
  • Simulation of various surface conditions (dry, wet, snow-covered, or icy road, mud, and so on)
  • Visual control/debug of parameters in real-time

There are also essential built-in components for traffic simulation (spatial triggers, pathfinding module).

Powerful C++ or C# API

Support for both C++ and C# programming languages provides decent flexibility for development teams. Both APIs are identical in terms of the access level:

  • Deep access to the rendering pipeline
  • Flexible multi-viewport mode
  • Extensive access to the scene graph and all parameters
  • CUDA support for fast GPU-CPU data transfer
  • Raw texture access
  • Extendible design for custom objects and shaders

Proven By Training Humans

UNIGINE 2 Sim has been proven for years in building professional simulators to train people. The SDK was designed to work as a part of modular distributed systems.

There are a lot of common tasks in generating virtual 3D environments for humans and AI.

A great variety of driving simulation systems created by our customers are installed worldwide. Cars, trucks, special vehicles, trains, military vehicles – all sorts of ground transportation simulators are powered by UNIGINE Engine.

Proven By Training Humans

Various Types Of Vehicles

Various Types Of Vehicles

Streamlined Content Workflow

  • WYSIWYG 3D scene (visual database) editor
  • Landscape tool with support for procedural data refinement
  • PBR workflow for 3D assets (compatible across modern engines)
  • Support for CAD and GIS data formats
  • 3D content library

Team Of Experts

UNIGINE team has been working with simulation & training tasks for more than ten years (and AI training-specific tasks for four years), having directly participated in many projects, receiving hands-on experience ourselves, and realizing many turnkey projects. 

All our experience was converted into UNIGINE 2 Sim software platform; so, our clients can use ready-made components that have been developed especially for solving similar tasks.

Our technical experts are always here to help your team with any questions.

Experts

UNIGINE Advantages Summary

  • Photorealistic image quality
  • Camera and sensor output
  • Automatic semantic data labeling
  • Easy scenario reconfiguration
  • Deep access to the rendering pipeline
  • Embeddable into C++ / C# codebase
  • Extremely performance-optimized
  • Georeferenced scenes support
  • A large number of out-of-the-box features
  • Visual scene editor + 3D content library
  • Generic vehicle dynamics simulation
  • Support for various types of vehicles
  • Proven in human-oriented simulators
  • Brought to you by experienced, enterprise-oriented experts

Autonomous Everywhere

Regardless of the type of autonomous vehicles, their AI should undergo a training process, facing all the same common challenges,
before they hit mass deployment:

  • Self-driving cars (SAE Level 4/Level 5)
  • Autonomous flying drones and UAV
  • Maritime autonomous surface ships and submarines
  • Autonomous spacecrafts

UNIGINE 2 Sim is capable to visualize all of these scenarios.

Autonomous Everywhere
Autonomous Everywhere

Developers from 250+ companies across all the continents use UNIGINE technologies to realize their projects.