tracking-by-detection, multiple object tracking algorithm

• mot3d

  1 8 0.0 Jupyter Notebook

  Fast Single View and Multiview Multi Object Tracking Using Minimum Cost Maximum Flow Formulation

  

This casts a multi-object object tracking problem as minimum-cost maximum flow problem: https://github.com/cvlab-epfl/mot3d

• yolo_tracking

  8 6,126 9.9 Python

  BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models

Try looking into DeepSort, which uses a deep association metric in addition to the traditional SORT algorithm to kind of improve upon the ID reassignment issue. However, I suspect you would have to come up with your own re-id model since you have a unique object you're trying to detect. Here's the paper . I've had decent results using https://github.com/mikel-brostrom/Yolov5_DeepSort_OSNet as an out of the box implementation for coco object. It's written in PyTorch.

• InfluxDB

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  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• cosine_metric_learning

  2 574 0.0 Python

  Deep Cosine Metric Learning for Person Re-identification

Hi! I have run into DeepSort but I think I am missing something. Once I opened this issue https://github.com/nwojke/cosine_metric_learning/issues/103 while trying to using it, but I think i was not so clear and the guy from DeepSort misunderstanded me. I saw that in DeepSort to train the appearance descriptor they use datasets which uses different views of the same object, for example the same white car will have both pictures in the training and in the test set. Instead I just have one photo for each instance. I think but I am not sure that this framework does not suit my problem due to this. Maybe I will post another question about this since It is a doubt that I am bringing with me.

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