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This document provides links to install each version of the Azure Kinect Body Tracking SDK.

Azure Kinect Body Tracking SDK contents

• Sep 21, 2017.
• V2.7.0.6 Key Updates: 1. Added Face Picture Comparison module to view the captured face pictures and the matched face picture in face picture library. Added Target Capture Alarm module to view the captured target pictures, such as face, human body, vehicle, etc.
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• Jan 28, 2019.

• Headers and libraries to build a body tracking application using the Azure Kinect DK.
• Redistributable DLLs needed by body tracking applications using the Azure Kinect DK.
• Sample body tracking applications.

Windows download links

Linux installation instructions

Currently, the only supported distribution is Ubuntu 18.04. To request support for other distributions, see this page.

First, you'll need to configure Microsoft's Package Repository, following the instructions here.

The libk4abt.-dev package contains the headers and CMake files to build against libk4abt.The libk4abt. package contains the shared objects needed to run executables that depend on libk4abt as well as the example viewer.

The basic tutorials require the libk4abt.-dev package. To install it, run

sudo apt install libk4abt1.0-dev

If the command succeeds, the SDK is ready for use.

Note

When installing the SDK, remember the path you install to. For example, 'C:Program FilesAzure Kinect Body Tracking SDK 1.0.0'. You will find the samples referenced in articles in this path.Body tracking samples are located in the body-tracking-samples folder in the Azure-Kinect-Samples repository. You will find the samples referenced in articles here.

Change log

v1.0.1

• [Bug Fix] Fix issue that the SDK crashes if loading onnxruntime.dll from path on Windows build 19025 or later: Link

v1.0.0

• [Feature] Add C# wrapper to the msi installer.
• [Bug Fix] Fix issue that the head rotation cannot be detected correctly: Link
• [Bug Fix] Fix issue that the CPU usage goes up to 100% on Linux machine: Link
• [Samples] Add two samples to the sample repo. Sample 1 demonstrates how to transform body tracking results from the depth space to color space Link; sample 2 demonstrates how to detect floor plane Link

v0.9.5

• [Feature] C# support. C# wrapper is packed in the nuget package.
• [Feature] Multi-tracker support. Creating multiple trackers is allowed. Now user can create multiple trackers to track bodies from different Azure Kinect devices.
• [Feature] Multi-thread processing support for CPU mode. When running on CPU mode, all cores will be used to maximize the speed.
• [Feature] Add gpu_device_id to k4abt_tracker_configuration_t struct. Allow users to specify GPU device that is other than the default one to run the body tracking algorithm.
• [Bug Fix/Breaking Change] Fix typo in a joint name. Change joint name from K4ABT_JOINT_SPINE_NAVAL to K4ABT_JOINT_SPINE_NAVEL.

v0.9.4

• [Feature] Add hand joints support. The SDK will provide information for three additional joints for each hand: HAND, HANDTIP, THUMB.
• [Feature] Add prediction confidence level for each detected joints.
• [Feature] Add CPU mode support. By changing the cpu_only_mode value in k4abt_tracker_configuration_t, now the SDK can run on CPU mode which doesn't require the user to have a powerful graphics card.

v0.9.3

• [Feature] Publish a new DNN model dnn_model_2_0.onnx, which largely improves the robustness of the body tracking.
• [Feature] Disable the temporal smoothing by default. The tracked joints will be more responsive.
• [Feature] Improve the accuracy of the body index map.
• [Bug Fix] Fix bug that the sensor orientation setting is not effective.
• [Bug Fix] Change the body_index_map type from K4A_IMAGE_FORMAT_CUSTOM to K4A_IMAGE_FORMAT_CUSTOM8.
• [Known Issue] Two close bodies may merge to single instance segment.

v0.9.2

• [Breaking Change] Update to depend on the latest Azure Kinect Sensor SDK 1.2.0.
• [API Change] k4abt_tracker_create function will start to take a k4abt_tracker_configuration_t input.
• [API Change] Change k4abt_frame_get_timestamp_usec API to k4abt_frame_get_device_timestamp_usec to be more specific and consistent with the Sensor SDK 1.2.0.
• [Feature] Allow users to specify the sensor mounting orientation when creating the tracker to achieve more accurate body tracking results when mounting at different angles.
• [Feature] Provide new API k4abt_tracker_set_temporal_smoothing to change the amount of temporal smoothing that the user wants to apply.
• [Feature] Add C++ wrapper k4abt.hpp.
• [Feature] Add version definition header k4abtversion.h.
• [Bug Fix] Fix bug that caused extremely high CPU usage.
• [Bug Fix] Fix logger crashing bug.

v0.9.1

• [Bug Fix] Fix memory leak when destroying tracker
• [Bug Fix] Better error messages for missing dependencies
• [Bug Fix] Fail without crashing when creating a second tracker instance
• [Bug Fix] Logger environmental variables now work correctly
• Linux support

v0.9.0

• [Breaking Change] Downgraded the SDK dependency to CUDA 10.0 (from CUDA 10.1). ONNX runtime officially only supports up to CUDA 10.0.
• [Breaking Change] Switched to ONNX runtime instead of Tensorflow runtime. Reduces the first frame launching time and memory usage. It also reduces the SDK binary size.
• [API Change] Renamed k4abt_tracker_queue_capture() to k4abt_tracker_enqueue_capture()
• [API Change] Broke k4abt_frame_get_body() into two separate functions: k4abt_frame_get_body_skeleton() and k4abt_frame_get_body_id(). Now you can query the body ID without always copying the whole skeleton structure.
• [API Change] Added k4abt_frame_get_timestamp_usec() function to simplify the steps for the users to query body frame timestamp.
• Further improved the body tracking algorithm accuracy and tracking reliability

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