Tracker	Technical Basis	Performance	Accuracy	Special Features	Application	MOTA Score (Benchmark)
BOOSTING Tracker	AdaBoost-based algorithm	Very slow	Low	Suitable only for legacy applications	Not recommended for modern applications	N/A (Generic type)
MIL (Multiple Instance Learning) Tracker	Ensemble Learning	Medium speed	Better than BOOSTING	Difficulties with error detection	Only useful in simple scenarios	N/A (Generic type)
KCF (Kernelized Correlation Filters) Tracker	Kernel-based correlation filters	Faster than BOOSTING/MIL	Medium quality	Difficulties with full occlusions	Suitable for medium speeds	N/A (Generic type)
CSRT (Channel and Spatial Reliability) Tracker	Discriminative Correlation Filters	Slightly slower than KCF	Higher than KCF	Better channel and spatial reliability	For precise tracking applications	N/A (Generic type)
MedianFlow Tracker	Optical Flow	Medium speed	Good at slow movements	Good error detection	Not suitable for fast objects	N/A (Generic type)
TLD (Tracking-Learning-Detection) Tracker	Tracking-Learning-Detection	Medium speed	Issues with false positives	Difficulties in OpenCV implementation	Not recommended	N/A (Generic type)
MOSSE (Minimum Output Sum of Squared Error) Tracker	Adaptive Correlation Filters	Very fast	Lower than CSRT/KCF	Optimized for speed	For real-time applications	N/A (Generic type)
GOTURN Tracker	Deep Learning (Caffe)	Hardware-dependent	Higher than traditional trackers	Requires separate Caffe model files	For resource-intensive applications	N/A (Generic type)
FastMOT	YOLO/SSD, Deep SORT + OSNet ReID, KLT, Kalman Filter, Numba optimization	Real-time (e.g., 42 FPS on MOT17-13)	High (66.8% MOTA)	Detector/Feature extractor skip (N frames), re-identifies out-of-frame objects, camera motion compensation, TensorRT backend	Real-time multi-object tracking, especially on embedded systems (e.g., Jetson) and scenes with moving cameras	66.8% (N=1)
FastTracker	Real Time and Accurate Visual Tracking	Very Fast	High	Online method using public detections	General real-time tracking	77.9
FLWM	IOF-Tracker: Two-Stage Multi-Targets Tracking	High	High	Using public detections	General multi-target tracking	77.7
FeatureSORT	Essential Features for Effective Tracking	High	High	Online method using public detections	General multi-target tracking	76.6
kalman_pub	(Likely Kalman Filter based) ByteTrack	Medium	Medium-High	Online method using public detections	Multi-Object Tracking by Associating Every Detection Box	67.0
OCSORTpublic	Observation-Centric SORT	Fast	Good	Rethinking SORT for Robust Multi-Object Tracking	General multi-object tracking	59.9
SORT20	Simple Online and Realtime Tracking	Real-time	Moderate	Online method using public detections	Simple and efficient multi-object tracking	42.7