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Tracker using kinematic Kalman filters.

Project description

Kinematic Tracker

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📖 Live docs: https://kovalp.github.io/kinematic-tracker-docs/

This tracker is based on kinematic Kalman filters. The system state can consist of multiple parts, each defined by its kinematic order and dimensionality. For example, to track cuboids aligned with Cartesian axes, we might decide for a constant-acceleration motion model for Cartesian coordinates and a constant-position motion model for the sizes of the cuboids. This choice encoded by orders = [3, 1]. The dimensionality of both parts (coordinates and sizes) is 3. Therefore dimensions = [3, 3] in our example.

The state of the cuboids aligned with Cartesian axis will have 12 variables. Internally, a block-diagonal states are used, i.e.

state = p_x, v_x, a_x, p_y, v_y, a_y, p_z, v_z, a_z, s_x, s_y, s_z

To simplify the input/output processing, one might find attractive a derivative-sorted order

state = p_x, p_y, p_z, s_x, s_y, s_z, v_x, v_y, v_z, a_x, a_y, a_z

This package provides utility classes for such conversion (block-diagonal ↔ derivative sorted).

Process noise models

The tracker supports various process noise models, including a custom adaptive process noise model based on a white-noise assumption.

Association metrics

A number of association metrics are implemented. Some of the metrics are experimental.

  • Mahalanobis with a process-measurement noise sum covariance (HPH + R) -- default.
  • 3D axes-aligned GIoU (volumetric GIoU for cuboids).
  • 3D yaw-only GIoU (volumetric GIoU for cuboids oriented by yaw).
  • Mahalanobis with size-modulated covariance (experimental).
  • IoU-like two-yaw (experimental): based on Mahalanobis distance with diagonal covariance.

Installation

If you plan to use OpenCV with HighGUI, then

pip install kinematic-tracker[gui]

If you do not plan to use OpenCV's GUI, then

pip install kinematic-tracker[headless]

In any case, you choose one extra: gui or headless.

Usage

Simple examples are available in the test/tutorials folder. The test folder is available in the source package

pip download kinematic-tracker --no-binary :all: --no-deps

Use the kinematic-tracker as dependency

uv add kinematic-tracker --extra headless

If you happen to need GUI-enabled version of OpenCV, then

uv add kinematic-tracker --extra gui

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