Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video matting of complex scenes
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Learning Parameterized Models of Image Motion
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Improved Adaptive Gaussian Mixture Model for Background Subtraction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2005 Papers
Bilayer Segmentation of Live Video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
On the Spatial Statistics of Optical Flow
International Journal of Computer Vision
Dynamosaicing: Mosaicing of Dynamic Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and video matting: a survey
Foundations and Trends® in Computer Graphics and Vision
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Video SnapCut: robust video object cutout using localized classifiers
ACM SIGGRAPH 2009 papers
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Foreground prediction for bilayer segmentation of videos
Pattern Recognition Letters
An attempt to segment foreground in dynamic scenes
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Discontinuity-aware video object cutout
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Integrating tracking with fine object segmentation
Image and Vision Computing
Improved image segmentation using motion
Proceedings of the 10th European Conference on Visual Media Production
TouchCut: Fast image and video segmentation using single-touch interaction
Computer Vision and Image Understanding
Hi-index | 0.00 |
Accurately modeling object colors, and features in general, plays a critical role in video segmentation and analysis. Commonly used color models, such as global Gaussian mixtures, localized Gaussian mixtures, and pixel-wise adaptive ones, often fail to accurately represent the object appearance in complicated scenes, thereby leading to segmentation errors. We introduce a new color model, Dynamic Color Flow, which unlike previous approaches, incorporates motion estimation into color modeling in a probabilistic framework, and adaptively changes model parameters to match the local properties of the motion. The proposed model accurately and reliably describes changes in the scene's appearance caused by motion across frames. We show how to apply this color model to both foreground and background layers in a balanced way for efficient object segmentation in video. Experimental results show that when compared with previous approaches, our model provides more accurate foreground and background estimations, leading to more efficient video object cutout systems.