- Finding with cars passing the mid-point (Approach #1 – Experimented with SQL)
- Take the bounding boxes between two frames and check the similarity between the matching regions. Between the two frames and the matching regions how much does the content match. This can be used to remove duplicate cars
- Generate a feature vector for the Area of Intersection and validate with the frame if it is similar.
- KNN approach – Experiment KNN approach with the data points to classify a new or existing object
- LSTM based tracking – Model the frames into sequences to classify if it is a new object or existing object. It is possible, Needs a bit more analysis
- Siamese network for Similarity of Objects
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