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Unsupervised Learning for Target Tracking and Background Subtraction in Satel...
Simulated data used to compare the performance of Jekyll and Hyde against a more traditional supervised Machine Learning approach. -
PETS sequence
The PETS sequence is a sequence of images with a static background and sparse foreground. The dataset is used to evaluate the performance of the proposed algorithm. -
Hall sequence
The Hall sequence is a sequence of images with a static background and sparse foreground. The dataset is used to evaluate the performance of the proposed algorithm. -
BMC2012 dataset
The BMC2012 dataset is a benchmark dataset for background subtraction in surveillance videos. -
UCSD Background Subtraction Dataset
UCSD background subtraction dataset contains videos with moving camera sequences. -
GraphBGS: Background Subtraction via Recovery of Graph Signals
Background subtraction is a fundamental pre-processing task in computer vision. This task becomes challenging in real scenarios due to variations in the background for both...
