Out-of-the-box code and models for CMU's object detection and tracking system for multi-camera surveillance videos. Speed optimized Faster-RCNN model. Tensorflow based. Also supports EfficientDet. WACVW'20
- Updated
Dec 16, 2022 - Python
Out-of-the-box code and models for CMU's object detection and tracking system for multi-camera surveillance videos. Speed optimized Faster-RCNN model. Tensorflow based. Also supports EfficientDet. WACVW'20
Real-time multi-object tracker using YOLOv7 and StrongSORT with OSNet
State-of-the-art model for person re-identification in Multi-camera Multi-Target Tracking. Benchmarked on Market-1501 and DukeMTMTC-reID datasets.
A multi-camera vehicle detection, tracking and re-identification system
[ICCV 2023] ReST: A Reconfigurable Spatial-Temporal Graph Model for Multi-Camera Multi-Object Tracking
This repo contains links to multi-person re-identification and tracking dataset in top view multi-camera environment.
A Low-cost Open-source High-speed Multi-camera Motion Capture System.
The main abnormal behaviors that this project can detect are: Violence, covering camera, Choking, lying down, Running, Motion in restricted areas. It provides much flexibility by allowing users to choose the abnormal behaviors they want to be detected and keeps track of every abnormal event to be reviewed. We used three methods to detect abnorma…
Official Implementation of "Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras"
Multi-camera Network research resources
live, low-latency markerless multi-camera 3D animal tracking system
[CVPRW 2023] "Leveraging Future Trajectory Prediction for Multi-Camera People Tracking"
Official Repo For "RockTrack"
Vehicle MTMC Tracking
JARVIS Markerless 3D Motion Capture Pytorch Library
This is the official Python and C++ implementation repository for a paper entitled "Track Initialization and Re-Identification for 3D Multi-View Multi-Object Tracking", Information Fusion (http://arxiv.org/abs/2405.18606).
TrackNet: A Triplet metric-based method for Multi-Target Multi-Camera Vehicle Tracking
Markerless Motion Capture Software is required to build the low-cost, modular and multi-camera ML-MoCap system.
Real-time multi-camera face tracking system with PyQt5 interface and alert notifications (including Telegram notifications). Supports webcams, RTSP streams, and provides face recognition with InsightFace models.
Tracking staff activities with multiple camera support by using yolo for the head, and using dlib for face recognition.
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