## 3 Methodology
### Confident Track Storage  
The confident track storage module is vital to the track management pipeline, ensuring the reliability of tracked identities over time. It selectively stores tracks with high confidence, enabling more effective management of active tracks and minimizing erroneous associations.  
**Track Confidence Calculation:** To determine whether a track should be stored as \"confident\", we introduce a confidence score \(C_{t}\) for each track \(t\), computed as a weighted combination of factors such as detection consistency, association reliability, and ReID match quality. The confidence score is defined as given in Equation (18):  
\[C_{t}=\alpha\cdot C_{det}+\beta\cdot C_{assoc}+\gamma\cdot C_{ReID} \tag{18}\]  
where  
* \(C_{det}\) represents the consistency of detections associated with the track. It is calculated as the ratio of successful detections to the total number of frames for which the track has been active.
* \(C_{assoc}\) represents the reliability of data associations for the track, measured by the inverse of the number of IDSws.
* \(C_{ReID}\) represents the quality of ReID matches, quantified by the average cosine similarity score \(S_{cos}\) of ReID matches over time.  
The parameters \(\alpha\), \(\beta\), and \(\gamma\) are empirically determined weights that balance the contribution of each factor, set to 0.4, 0.3, and 0.3 respectively, reflecting the relative importance of detection consistency, association reliability, and ReID match quality in establishing track confidence.  
**Empirical Threshold for Confidence:** A track is classified as confident if its confidence score \(C_{t}\) exceeds a predefined threshold \(\tau_{conf}\), empirically set at 0.7 based on validation experiments. This threshold ensures that only tracks with a high level of reliability are stored, reducing the risk of storing incorrect or noisy tracks as given in Equation (19).  
\[Confident\quad Track\quad t\quad\text{if}\quad C_{t}>\tau_{conf} \tag{19}\]  
**Storage Mechanism and Interaction with Other Modules:** Once a track is classified as confident, it is stored in the confident track storage module, which acts as a repository for high-quality tracks. This allows for the reactivation of tracks if the same object is detected later, enhancing identity management across long sequences. The interaction between the confident track storage and other modules is twofold:  
* **Data Association:** During the data association process, confident tracks in storage are prioritized for matching with new detections. This reduces the likelihood of identity switches and enhances track continuity.  
Zero-Shot ReID Integration: In cases where a track has been lost and subsequently reappears, the zero-shot ReID module can utilize the embeddings of confident tracks to reassociate the object with its previous identity, further ensuring consistent identity tracking across the entire sequence.  
Incorporating the confident track storage module improves the overall tracking system's reliability and stability, as these confident tracks serve as anchor points, reducing errors and enhancing long-term identity preservation. Empirical tuning of confidence thresholds and weighting parameters ensures effective adaptation to diverse tracking scenarios, maintaining a balance between precision and recall.  
Tracks with high confidence and stable identity are stored in the confident track storage (CTS) for future reference as given in Algorithm 5. Low-confidence or outdated tracks are removed to maintain efficient storage and improve tracking reliability in dynamic and complex scenes.  
```
0: Updated tracks \(T_{t}\), Confident Track Storage (CTS)
0: Updated CTS
1:for each track \(t_{k}\in T_{t}\)do
2:if\(t_{k}\) has high confidence and stable identity then
3: Add \(t_{k}\) to CTS
4:endif
5:endfor
6: Remove obsolete or low-confidence tracks from CTS
7:return CTS
```  
**Algorithm 5** Confident Track Storage