Real-Time Video Tracking Framework With Moving Object Segmentation in Stream Data

K. R. Manjula; S. Anand Kumar Varma

doi:10.1007/978-981-16-1941-0_76

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Real-Time Video Tracking Framework With Moving Object Segmentation in Stream Data

K. R. Manjula S. Anand Kumar Varma

Year: 2021 Lecture notes in networks and systems Pages: 745-757 Publisher: Springer International Publishing

DOI: 10.1007/978-981-16-1941-0_76

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Keywords:

Artificial intelligence Computer vision Computer science Segmentation Video tracking Cluster analysis Object (grammar) Tracking (education) Frame (networking) Feature (linguistics) Segmentation-based object categorization Shadow (psychology) Image segmentation Scale-space segmentation Displacement (psychology) Pattern recognition (psychology)

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Topics

Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Video Analysis and Summarization

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Real-Time Video Tracking Framework With Moving Object Segmentation in Stream Data

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