DeepSORT based Tracking is based on the following steps: Detection: Before objects can be tracked in each frame, they must be detected. This is done using a standard object detector like Faster R-CNN. Feature Extraction: Extract features from the detected objects. These features will help to match objects across frames. Data Association: Match detected objects with tracked objects from previous frames using both the bounding box overlap (using the Hungarian algorithm) and the feature similarity. Track Management: Update tracks or create/delete tracks as necessary.
Tasks: Object Detection, Feature Extraction, Multimodal
Task Categories: Computer Vision