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Foreground detection using motion histogram threshold algorithm in high-resolution large datasets
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DOI：10.1007/s00530-020-00676-3.png)
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Abstract
En 中文
Background subtraction, being the most cited algorithm for foreground detection, encounters the major problem of proper threshold value at run time. For effective value of the threshold at run time in background subtraction algorithm, the primary component of the foreground detection process, motion is used, in the proposed algorithm. For the said purpose, the smooth histogram peaks and valley of the motion were analyzed, which reflects the high and slow motion areas of the moving object(s) in the given frame and generates the threshold value at run time by exploiting the values of peaks and valley. This proposed algorithm was tested using four recommended video sequences, including indoor and outdoor shoots, and were compared with five high ranked algorithms. Based on the values of standard performance measures, the proposed algorithm achieved an average of more than 12.30% higher accuracy results.
Keywords:
Background subtract
Foreground detection
Intelligent video surveillance
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