비디오 추적

Read camera image sequences and import ground truth and detections in MOT Challenge format.

Implement the Simple Online and Realtime (SORT) object tracking algorithm.

Integrate appearance features from a re-Identification (Re-ID) Deep Neural Network with a multi-object tracker to improve the performance of camera-based object tracking. The implementation closely follows the Deep Simple Online and Realtime (DeepSORT) multi-object tracking algorithm [1]. This example uses the Sensor Fusion and Tracking Toolbox™ and the Computer Vision Toolbox™.

Resolve challenging tracking scenarios when objects are occluded and in close proximity.

Track people throughout a video sequence using re-identification with a residual network.

Create an automation algorithm to automatically label data for object tracking and for object re-identification.

Convert a groundTruth object to the trackCLEARmetrics truth format.

Convert a groundTruth object to the re-identification training data format.

Detect multiple people, track them, and estimate their body poses in a video by using pretrained deep learning networks and a global nearest-neighbor (GNN) assignment tracking approach.