Spectacular AI
State-of-the art inside-out tracking for AR/VR/XR, drones, and ground vehicles.
Spectacular AI SDK
Low power
Runs real-time on embedded hardware
Standalone
No dependencies to ARKit, ARCore, or specific hardware
Accurate
State-of-the-art performance, see below
For off-the-shelf devices
- Plug'n'play experience, low-level details are handled by the SDK
- Easy-to-use C++ and Python SDKs with extensive examples
- Free for non-commercial use, contact us for commercial pricing
For custom hardware
- Our core C++ SDK can support any device with suitable camera, IMU and compute hardware
- Minimum CPU requirement: 2x ARM Cortex A53. Can leverage embedded DSPs/NPUs for acceleration
- Additional supported sensors: Lidar and RTK-GPS
- Integration and hardware design support available on request
Runs on
Spectacular AI SDK in action
Inside-out tracking
Accurate and low-latency 6-DoF pose tracking for AR & VR headsets, without external lighthouses. Lightweight enough to run on an embedded processor in the headset.
Drone navigation
Runs real-time on embedded devices. Ideal as an input for autonomous navigation. Power consumption well below 1 W with correct acceleration.
GNSS-VIO
Optional fusion with GNSS allows uninterrupted positioning during GPS outages and provides accurate orientation, even with a single GPS antenna.
Large-scale mapping
A floor area of approximately 1000m² was mapped in 21 minutes using Azure Kinect device.
Research
Visual-inertial navigation done right
Whether your challenge is to track the movement of vehicles, people or autonomous things—you will need to understand the device's relative location in the surrounding 3D environment.
Our methods are learning-based and adapt to uncertainties in the observed data. We do principled probabilistic inference, where both visual and inertial data contribute as equal parties. Our unique approach is built from scratch using first-principles and implemented using state-of-the-art computer vision and machine learning methods.
Related research
O. Seiskari, P. Rantalankila, J. Kannala, J. Ylilammi, E. Rahtu, A. Solin
HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry
2022 IEEE Winter Conference on Applications of Computer Vision (WACV)
A. Solin, S. Cortés, E. Rahtu, J. Kannala
PIVO: Probabilistic Inertial-visual Odometry for Occlusion-robust Navigation
2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
A. Solin, S. Cortés, E. Rahtu, J. Kannala
Inertial Odometry on Handheld Smartphones
2018 21st International Conference on Information Fusion (FUSION)
S. Cortés, A. Solin, E. Rahtu, J. Kannala
ADVIO: An Authentic Dataset for Visual-Inertial Odometry
2018 European Conference on Computer Vision (ECCV)
Team
Spectacular AI is a university spin-off company from Helsinki, founded in 2021.
Our team is a unique mixture of seasoned software professionals plus established computer vision and machine learning researchers. We solve challenging problems related to Computer Vision, Spatial AI, Sensor Fusion and SLAM.
