Memory-based moving object extraction for video indexing

Roy Ruoyu Wang, Pengyu Hong, Thomas Huang

Research output: Contribution to journalArticlepeer-review

Abstract

Extracting moving objects from a video shot provides a good low-level representation of videos. It provides object trajectory, color, shape characteristics. Combined with specific domain knowledge, it can be a powerful cue as what is going in a video shot. This paper proposes a unsupervised moving object extraction/tracking system that attempts to capture salient moving objects from an image sequence. The novelty of the proposed system lies in that it requires no object initialization and it is aimed to tolerate noisy segmentations at individual frame level. A temporal stack structure is used as a memory device to filter and learn salient objects. The learning of moving object takes a bottom-up approach, moving from independent motion segmentation results at each frame level to a learned whole object characteristics.

Original languageEnglish (US)
Pages (from-to)811-814
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Volume15
Issue number1
StatePublished - Dec 1 2000

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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