Setting and optimizing parameters for 3D Tracking

Object Detection

The basis of 3D Tracking is a 2D object detection procedure, usually performed on simultaneously acquired images from at least two cameras.

Object detection is based on background subtraction and feature extraction. In Braid, these parameters are typically set in the .toml config file specified when starting the program. When not explicitly specified, default parameters are used. Within Strand Camera, including when run from within Braid, these parameters can be set in a running instance. The parameters are specified in a camera-specific way, meaning that each camera can have its own parameter values.

In Strand Camera, the option Record CSV file will record the object detection results in CSV format with a header including the object detection parameters in use at the start of the recording.

The details on implementation and parameters can be found in the ImPtDetectCfg section of the API.

A more technical account of this procedure can be found in Straw et al. (2011).

3D Tracking

3D tracking is based on data association, which links 2D features from individual cameras to a 3D model, and an Extended Kalman Filter, which updates the estimated position and velocity of the 3D model from the 2D features.

The implementation details for the 3D tracking procedures can be found in the TrackingParams section of the API.