For many tracking and surveillance applications, background subtraction provides an effective means of segmenting objects moving in front of a static background. Researchers have traditionally used combinations of morphological operations to remove the noise inherent in the background-subtracted result. Such techniques can effectively isolate foreground objects, but tend to lose fidelity around...

In this paper, we present a novel feature point based stereo matching algorithm with global energy minimization. The initial disparity map is estimated by considering matching SURF key points between two images inside each homogeneous colour region by an adaptive box matching approach. Next, we improve the initial disparity map with a RANSAC based plane fitting technique which relies on accurac...

Baker’s technique, which was created over three decades ago, is a powerful tool for designing polynomial time approximation schemes (PTAS) for NP-hard optimization problems on planar graphs and their generalizations. In this paper, we propose a unified framework to formulate the optimization problems where the local constraints of these problems are encoded by functions attached on the vertices...

Structure learning algorithms usually focus on the compactness of the learned model. However, for general compact models, both exact and approximate inference are still NP-hard. Therefore, the focus only on compactness leads to learning models that require approximate inference techniques, thus reducing their prediction quality. In this paper, we propose a method for learning an attractive clas...

An important problem in medical image analysis is the segmentation of anatomical regions of interest. Once regions of interest are segmented, one can extract shape, appearance, and structural features that can be analyzed for disease diagnosis or treatment evaluation. Diffusion tensor magnetic resonance imaging (DT-MRI) is a relatively new medical imaging modality that captures unique water dif...

Given two stereo images of a scene, it is possible to recover a 3D understanding of the scene. This is the primary way that the human visual system estimates depth. This process is useful in applications like robotics, where depth sensors may be expensive but a pair of cameras is relatively cheap. In order to construct depth maps from stereo images, we need to first solve the stereo corresponde...

The standard graph cut technique is a robust method for globally optimal image segmentation. However, because of its global nature, it is prone to capture outlying areas similar to the object of interest. This paper proposes a novel method to constrain the standard graph cut technique for tracking objects in a region of interest. By introducing an additional penalty on pixels based upon their d...

Introduction. Removal of non-brain tissues, particularly dura, is an important step in enabling accurate measurements of brain structures. Previous approaches (2,5,6) can lead to brain loss and/or leave residual dura (4), posing a problem for subsequent cortical thickness estimation. Brain loss cannot be reversed downstream in the segmentation pipeline. Inclusion of dura mater can cause overest...

Correlation Clustering is an elegant model that captures fundamental graph cut problems such as Min s − t Cut, Multiway Cut, and Multicut, extensively studied in combinatorial optimization. Here, we are given a graph with edges labeled + or − and the goal is to produce a clustering that agrees with the labels as much as possible: + edges within clusters and − edges across clusters. The classica...

In this paper, we present a graph cut-based motion segmentation method that takes occlusion into account. We formulate the motion segmentation problem in terms of energy minimization with accounting for occlusion and minimize the energy function with the divisive graph cut algorithm where multiway minimum cuts for motion segmentation are efficiently computed through the swap move and split move...