Estimating border ownership using iterative vector voting and conditional random fields

Özkan, Buğra
Border ownership is the information that signifies which side of a border owns the border. Estimating this information has recently become very popular for perceptual organization as it allows rectification of ambigious visual information. It is applied on many computer vision problems such as object detection, depth perception and optical flow. In this thesis, two different approaches are followed to solve the border ownership problem. For the supervised approach, conditional random fields are used as it is the most appropriate method for modelling con- textual relations between semantic classes. Tensor voting is the inspire of our second algorithm called Iterative Vector Voting, as it allows modelling different information sources and their interactions. It is an unsupervised voting frame- work, which is proper for the use of Gestalt visual cues. Experiments show that both two models show significant contribution to the border ownership problem with respect to the successful results gathered on our own large-scale dataset.


Analysis of methods for border ownership estimation
Olgunsoylu, Sertaç; Kalkan, Sinan; Department of Computer Engineering (2015)
Border Ownership (BO) signifies which side of an image border owns the border. This information is very important for many computer vision problems. There are various approaches for estimating BO in the literature. One approach is to use methods that rely on low-level local features; combinations of local visual cues such as convexity or junctions and using spectral features have been proven to be quite effective. Alternatively, global constraints or cues can be imposed on top of local cue predictions to ma...
Analysis of border ownership cues and improvement of depth prediction using border ownership
Akkuş, Mehmet Akif; Kalkan, Sinan; Department of Computer Engineering (2014)
Border Ownership is the problem of identifying which image regions own the image border. This information is essential and important for large variety of high-level vision problems such as object segmentation, object recognition, depth perception, motion perception etc. Current computational approaches to Border Ownership (BO) estimation either use artificial or limited number of real images. In this thesis, we propose a new comprehensive BO database, including 500 indoor and 500 outdoor images whose BO inf...
Extraction of border ownership information by conditional random field model Koşullu rastgele alan modeli ile sinir sahipligi bilgisi çikarimi
Özkan, Bugra; Kalkan, Sinan (2013-04-26)
Border ownership is a kind of information used for determining the regions that own borders in an image. This information has recently become more valuable as it began to be used in many vision problems such as figure-ground segregation, depth perception and optical flow, however the quality and quantity of current literature are not sufficient yet. In this study, a Conditional Random Field model is developed for the enhancement of border ownership labelings, which are extracted with the help of some spatia...
A comprehensive database for border ownership Sinir Sahiplǐgi Için Kapsamli Bir Veri Taban
Akkuş, Mehmet Akif; Topuz, Gaye; Özkan, Bǔgra; Kalkan, Sinan (2013-04-26)
Border ownership is a problem of identifying which visual region the borders of a visual image belong. It has valuable and essential information for visual systems. Existing computational approaches either use artificial or limited type and number of images. In this study, we propose a new comprehensive database, which contains border ownership information from the edges and segments of 500 indoor and 500 outdoor images determined by hand-labeling of human participants and a couple of analyses carried on th...
The role of geographical limitation with respect to asylum and refugee policies within the context of Turkey̕s EU harmonization process
Tarımcı, E. Alper; Kip Barnard, Fulya; Department of European Studies (2005)
Turkey has been among a limited number of states that signed the 1951 Convention Relating to the Status of Refugees and adopted the geographical limitation; furthermore, among a very few number of states that still maintains this limitation. The aim of this thesis is to analyze the significance of geographical limitation and what has brought the changes to Turkish asylum policies in respect of this reservation. Turkey is expected to abolish the geographical limitation during the European Union harmonization...
Citation Formats
B. Özkan, “Estimating border ownership using iterative vector voting and conditional random fields,” M.S. - Master of Science, Middle East Technical University, 2014.