Back to Search
Start Over
Practical automatic background substitution for live video
- Source :
- Computational Visual Media, Vol 3, Iss 3, Pp 273-284 (2017)
- Publisher :
- Springer Nature
-
Abstract
- In this paper we present a novel automatic background substitution approach for live video. The objective of background substitution is to extract the foreground from the input video and then combine it with a new background. In this paper, we use a color line model to improve the Gaussian mixture model in the background cut method to obtain a binary foreground segmentation result that is less sensitive to brightness differences. Based on the high quality binary segmentation results, we can automatically create a reliable trimap for alpha matting to refine the segmentation boundary. To make the composition result more realistic, an automatic foreground color adjustment step is added to make the foreground look consistent with the new background. Compared to previous approaches, our method can produce higher quality binary segmentation results, and to the best of our knowledge, this is the first time such an automatic and integrated background substitution system has been proposed which can run in real time, which makes it practical for everyday applications.
- Subjects :
- Brightness
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Binary number
Boundary (topology)
02 engineering and technology
lcsh:QA75.5-76.95
alpha matting
Computer graphics
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
Segmentation
Computer vision
background subtraction
Background subtraction
business.industry
Substitution (logic)
020207 software engineering
background replacement
Mixture model
Computer Graphics and Computer-Aided Design
020201 artificial intelligence & image processing
lcsh:Electronic computers. Computer science
Computer Vision and Pattern Recognition
Artificial intelligence
business
background substitution
Subjects
Details
- Language :
- English
- ISSN :
- 20960433
- Database :
- OpenAIRE
- Journal :
- Computational Visual Media
- Accession number :
- edsair.doi.dedup.....f48058df5a6ac6c0014c84204d58cff4
- Full Text :
- https://doi.org/10.1007/s41095-016-0074-0