The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Semiautomatic segmentation and tracking of semantic video objects
Abstract
This paper introduces a novel semantic video object extraction system using mathematical morphology and a perspective motion model. Inspired by the results from the study of the human visual system, we intend to solve the semantic video object extraction problem in two separate steps: supervised I-frame segmentation, and unsupervised P-frame tracking. First, the precise semantic video object boundary can be found using a combination of human assistance and a morphological segmentation tool. Second, the semantic video objects in the remaining frames are obtained using global perspective motion estimation and compensation of the previous semantic video object plus boundary refinement as used for I frames.
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Cites
A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
Nearest neighbor pattern classification
Cover, T., & Hart, P. (1967) · IEEE Transactions on Information Theory · doi:10.1109/tit.1967.1053964 · Cited by 16,936
Hierarchical Model-Based Motion Estimation
Anandan, P., Bergen, J. R., Hanna, K. J., & Hingorani, R. (1993) · Motion Analysis and Image Sequence Processing · doi:10.1007/978-1-4615-3236-1_1 · Cited by 193
Cited by
Unsupervised extraction of visual attention objects in color images
Han, J., Ngan, K. N., Li, M., & Zhang, H.-J. (2006) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2005.859028 · Cited by 406
Fast and automatic video object segmentation and tracking for content-based applications
Kim, C., & Hwang, J.-N. (2002) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/76.988659 · Cited by 304
Metadata
- Authors
- Gu, C., & Lee, M.-C.
- Venue
- IEEE Transactions on Circuits and Systems for Video Technology
- Published
- 1998
- Volume
- 8
- Issue
- 5
- Pages
- 572-584
- ISSN
- 1051-8215 (ISSN-L)
- OpenAlex
- W2120599612
- Cited by
- 234
- References
- 3
- FWCI
- 18.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
