Overview
Intel® SceneScape unlocks business applications from raw sensor data by providing an abstraction layer built on a digital twin of each scene. Objects, people, and vehicles within the scene are represented as overlays on the dynamic structure of the digital twin. Applications, autonomous systems, and mobile systems securely access the digital twin abstraction layer to make decisions about the state of the scene, such as whether a person is in danger, a part is worn or broken, someone has been waiting in line too long, a product has been mis-shelved, or a child has called out for help. Powerful AI algorithms and AI hardware crunch all available sensor data to maintain the 4D scene graph (3D plus time), as quickly and accurately as possible. With Intel® Distribution of OpenVINO™ toolkit, Intel® SceneScape is able to use raw sensor data to create the 4D semantic digital replica by ingesting detections from 2D cameras and mapping them into the abstraction layer. The Intel® Distribution of OpenVINO™ toolkit also helps to abstract the different types of Intel® hardware accelerators, including CPU, GPU, VPU, FPGA, and GNA, enabling developers to write code once and deploy it.
Highlights
- Scene Context: Scene and Sensor Management utilizes knowledge about sensors to apply scene context. For example, the position of a smart camera in a building allows for mapping the context of detected people from the camera view into building coordinates.
- Multimodal detection: Multimodal tracking allows users to decide what sensors best fit their operational needs. Intel SceneScape readily handles visual, infrared, radio frequency (RF), Intel® RealSense™ tracking and depth sensing cameras, or even other environmental sensors.
- Multi-sensor data fusion: Multiple sensor fusion means Intel SceneScape will detect an object of interest at multiple angles in different sensors but know to only display the object of interest once on the scene graph removing duplicates and reducing error.
Details
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Dimension | Cost/hour |
---|---|
c7i.2xlarge Recommended | $0.00 |
c7i.8xlarge | $0.00 |
c7i.16xlarge | $0.00 |
c7i.48xlarge | $0.00 |
m7i.2xlarge | $0.00 |
m7i.metal-24xl | $0.00 |
m7i.4xlarge | $0.00 |
m7i.8xlarge | $0.00 |
m7i.12xlarge | $0.00 |
m7i.xlarge | $0.00 |
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
New in this release
- Percebro, Scene Controller, Scene Manager and auto calibration docker images can be built independently.
- SceneScape can be deployed using third-party mosquitto broker.
- Scene Controller can simultaneously work with object detections from Percebro and Deep Learning Streamer Pipeline Server.
- Except for scene manager service at initialization, all other services can operate independent of each other.
- Better tracker scaling with increasing object categories
- Reduced docker image sizes
- Revised documentation
- Bug fixes
Additional details
Usage instructions
- Connect to the instance via SSH with the username ubuntu
- Run the setup script: ./setup.sh in the user home directory 3 Fill in your account details and wait for the installation to complete
- Once setup is complete, navigate to a web browser and connect to https://your-EC2-instance-IP-or-hostname and login with the username admin.
Please report and discuss any issues though the link below: https://github.com/open-edge-platform/scenescape/issues
Note: The Scenescape application is set to start automatically on subsequent reboots
Support
Vendor support
Github Project: https://github.com/open-edge-platform/scenescape User Guide: https://github.com/open-edge-platform/scenescape/blob/main/docs/user-guide/Overview.md
V1.3.0: https://github.com/open-edge-platform/scenescape/releases/tag/v1.3.0
Open Edge Platform - SceneScape TOC:
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