Fast and automatic video object segmentation and tracking for content-based applications
By Changick Kim, Jenq-Neng Hwang. IEEE Trans. Circuits Syst. Video Technol., 2002
362 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/8c0918f9801c7053ab7b750eefcf311488b47114
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Ioannis Pitas
- N. Nikolaidis
- Frank D. Wood
- Costas I. Cotsaces
- Willie Neiswanger
- Colin White
- Yash Savani
- Sam Nolen
Citations in the corpus
- Unsupervised Detection and Tracking of Arbitrary Objects with Dependent Dirichlet Process Mixtures (2012, methodology): “These methods might be placed into a few broad categories: those that aim to distinguish the foreground regions of images from the background [33, 12, 65, 39], segment images into distinct regions to perform localization [35, 23, 56], track an object over a sequence of images (after its position has”
- Video shot detection and condensed representation. a review (2006, methodology): “Kim and Hwang [18]. They use the method described in [ 19 ]”