Implementation of Trackers to handle multi-camera videos
To implement a tracking system for Trackers to handle multi-camera video streams, the following methods can be used:
- multiprocess architecture: Create separate processing processes for each camera source, utilizing Python's multiprocessing module.
- GPU Resource Allocation: If GPU acceleration is used, make sure that each process gets enough CUDA stream resources.
- Central ID Management: Set up a centralized tracking ID server to coordinate the target matching problem among different cameras.
- Performance Monitoring: Establish monitoring mechanisms to ensure that system resources are not overloaded by excessive video streaming.
For specific implementations, middleware such as Redis can be considered to cache and share the tracking state across cameras. For advanced applications that require cross-camera tracking, ReID (Re-Identification) technology can be integrated.
This answer comes from the articleTrackers: open source tool library for video object trackingThe
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