Motion detection (MD) is a fundamental step in many advanced computer vision applications, but the various complex challenges in real surveillance videos lead to some false positives and false negatives in the detection results of traditional MD algorithms. Therefore, joint instancewise and instance-union fusion for improving MD algorithms, in which an instance segmentation model is combined with a traditional MD algorithm. are proposed to address this problem. First, for each input frame (indexed by t), the MD algorithm produces a binary mask Mt, and the instance segmentation model produces the specific categories of binary instance masks (BIMs). Second, according to the instance confidence, BIMs are divided into high-quality binary instance masks (HBIMs) and low-quality binary instance masks (LBIMs). Then instancewise fusion of HBIMs with Mt and instance-union fusion of LBIMs with Mt are used to generate a high-quality foreground segmentation mask |
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CITATIONS
Cited by 1 scholarly publication.
Detection and tracking algorithms
Video
Fermium
Frequency modulation
Image segmentation
Motion detection
Binary data