<p>In DeepSORT, you need to have detection in order to perform tracking. It is a tracking-by-detection method. The detection results are input to the Kalman filter component of DeepSORT. The filter generates tracking predictions. Also, the bounding boxes from detection are used to extract crops of RoI from the input image. These image crops are used by the trained Siamese model for feature extraction. The feature extraction by the Siamese model helps in reducing ID Switch.</p>
<p>If you are only interested in doing tracking and ID switch in case of occlusion is not your concern then you can have look at <a href="https://arxiv.org/abs/2004.01177" rel="nofollow noreferrer">CenterTrack</a>. It does joint detection and tracking in a single model. In this case, you can avoid model training from scratch. The authors provide pre-trained models for tracking both pedestrians and vehicles. As compared to DeepSORT the CenterTrack is pretty fast. </p>
Can I use DeepSORT without deep learning detection such as YOLO?
<p>I am new to computer vision, and I still didn't try any kind of neural network detections such as yolo, however, I am wishing to do object tracking before entering the field of detection. I started reading about deep sort and all the projects use deep learning detections that needs training. My question is, can I give an ROI result to my deep SORT tracker instead of detections using YOLO and it continues tracking the object selected with ROI.</p>
<p>Here is a link that i found information about the code of DeepSORT.<a href="https://nanonets.com/blog/object-tracking-deepsort/" rel="nofollow noreferrer">DeepSORT: Deep Learning to Track Custom Objects in a Video</a></p>