Abstract
Alpha matting is an ill-posed problem, as such the user must supply dense partial labels for an acceptable solution to be reached. Unfortunately this labelling can be time consuming. In this paper we introduce the w-penalty function, which when incorporated into existing matting techniques allows users to supply extremely sparse input. The formulated objective function encourages driving matte values to 0 and 1. The experiments demonstrate the proposed model outperforms the state-of-the-art KNN matting algorithm. MATLAB code for our proposed method is freely available in the MatteKit package1..
Original language | English |
---|---|
Title of host publication | Proceedings of the 2014 International Conference on Digital Image Computing: Techniques and Applications |
Place of Publication | United States |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1-7 |
Number of pages | 7 |
ISBN (Electronic) | 9781479954094 |
DOIs | |
Publication status | Published - 2014 |
Event | 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) - Novotel Wollongong Northbeach Hotel, Wollongong, Australia Duration: 25 Nov 2014 → 27 Nov 2014 https://ssl.informatics.uow.edu.au/dicta2014/ |
Conference
Conference | 2014 International Conference on Digital Image Computing |
---|---|
Country/Territory | Australia |
City | Wollongong |
Period | 25/11/14 → 27/11/14 |
Other | The International Conference on Digital Image Computing: Techniques and Applications (DICTA) is an International Conference on computer vision, image processing, pattern recognition, and related areas. DICTA was established as a biennial conference in 1991 and became an annual event in 2007. It is the premier conference of the Australian Pattern Recognition Society (APRS). |
Internet address |