In this article (and the companion github repo : mpdroid/bones), we explore use of this kit with Azure Cognitive Services to enhance how a person can interact with objects around them in 3-dimensional space.
The kit provides hardware/software to capture videos in color/depth and to extract body tracking information from them. In this article (and the companion github repo : mpdroid/bones``), we explore use of this kit with Azure Cognitive Services to enhance how a person can interact with objects around them in 3-dimensional space.
The hardware device is supported by two SDKs:
Thempdroid/bones project includes a few applications that demonstrate the dev kit capabilities. The README in the github repo provides a detailed list of instructions to download, build and run the project. While the project was developed on Ubuntu 20.04, it should work on lower Linux versions and Windows. These are the pre-requisites:
AZURE_VISION_KEYenvironment variables respectively.
The project also makes use of a few external libraries that are either embedded with the source code or get downloaded when you git clone it with the
— recursive option;
The diagram below shows how the code is organized.
Euclidwraps body tracking API and implements the geometry.
Renderorhandles presenting camera frames with annotations on application window.
*Sceneclasses implement scene comprehension and annotation.
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Computer Vision (CV) is nowadays one of the main application of Artificial Intelligence (eg. Image Recognition, Object Tracking, Multilabel Classification). In this article, I will walk you through some of the main steps which compose a Computer Vision System.