Skeleton-based supplementation for foreground image segmentation
作者： Lim Se Hoon , Large Timothy Andrew
DOI:
关键词: Computer vision 、 Image (mathematics) 、 Skeleton (category theory) 、 Image segmentation 、 Artificial intelligence 、 Computer science
摘要: Systems and methods for foreground image segmentation, which receive data captured at a first time, generate skeleton model of subject in the data, an initial mask segment including subject, secondary points corresponding to identify supplemental based on least model, combine with obtain combined mask, apply portion subject.
lens.org 参考文章(47)
Charles Byers, Jim Chou, Rohit Puri, Adaptation of video for use with different number of cameras and displays at endpoints ,(2011)
Bruce L. Davis, Methods and arrangements for sensing identification information from objects ,(2011)
Antonio Criminisi, Jamie Daniel Joseph Shotton, Toby Sharp, Andrew Fitzgibbon, Matthew Darius Cook, Foreground and Background Image Segmentation ,(2010)
Dennis Jinn Lin, Sanjay Jeram Patel, Minh Ngoc Do, Daniel Palmer Dabbelt, Quang Huu Nguyen, System for background subtraction with 3D camera ,(2014)
Aravind Sundaresan, Ramalingam Chellappa, Method and system for markerless motion capture using multiple cameras ,(2007)
Yogesh Manav, Rajaram Hanumantacharya Naganur, Pavan Sudheendra, Rajagopalan Venkata Raghavan, Shubham Baidvanath Bhattacharya, Apparatus and method for composing images in an image processing device ,(2012)
Nebojsa Jojic, Charles Zitnick, Sing Bing Kang, Simultaneous optical flow estimation and image segmentation ,(2005)
Howard I. Cannon, Christopher J. Buehler, Intelligent camera selection and object tracking ,(2006)
Charles Claudius Marais, Zsolt Mathe, Environment and/or Target Segmentation ,(2013)
Carsten Curt Eckard Rother, Andrew Blake, Padmanabhan Anandan, Foreground extraction using iterated graph cuts ,(2004)