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Detecting and tracking multiple objects in a video in real-time can be tricky. Luckily, the computer vision community has developed object-tracking algorithms to tackle this task over the years. These algorithms aim to identify and follow objects as they move through a video.
A great example of these algorithms is ByteTrack. It can detect and continuously track multiple objects by giving each one a unique ID. Unlike other algorithms, ByteTrack considers all detected objects (not just high-confidence ones). By doing so, it can improve its tracking accuracy even in challenging conditions like occlusion.
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Bytes is a robust computer vision tracking technique that excels at multiple target objects tracking, including dealing with occlusion and tracking precision loss. In the real application for instance, this method supports 3D scene tracking within different scenes. This robust methodology can handle tracking across videos and different angles and speeds are supported.
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