Junhwan Kim - Profile on Academia.edu (original) (raw)

Papers by Junhwan Kim

Method and system for subscribing to digital broadcasting service through mobile communication network

Apparatus and method for extracting context and providing information based on context in multimedia communication system

Method and System for Providing Information Based on Logo Included in Digital Contents

Method, Apparatus, and Computer Readable Recording Medium for Acquiring Information on Products Attached to Person in Image Data

Apparatus and method for automatically managing and performing schedule

Visual Correspondence Using

We address visual correspondence problems without assumingthat scene points have similar intensit... more We address visual correspondence problems without assumingthat scene points have similar intensities in differentviews. This situation is common, usually due tonon-lambertian scenes or to di# erences between cameras. We use maximization of mutual information, apowerful technique for registering images that requiresno apriorimodel of the relationship between scene intensitiesin di# erent views. However, it has provendi# cult to use mutual information to compute densevisual correspondence. Comparing fixed-size windowsvia ...

Proceedings Ninth IEEE International Conference on Computer Vision, 2003

We address visual correspondence problems without assuming that scene points have similar intensi... more We address visual correspondence problems without assuming that scene points have similar intensities in different views.This situation is common, usually due to non-lambertian scenes or to differences between cameras. We use maximization of mutual information, a powerful technique for registering images that requires no a priori model of the relationship between scene intensities in different views. However, it has proven difficult to use mutual information to compute dense visual correspondence. Comparing fixed-size windows via mutual information suffers from the well-known problems of fixed windows, namely poor performance at discontinuities and in low-texture regions. In this paper, we show how to compute visual correspondence using mutual information without suffering from these problems. Using a simple approximation, mutual information can be incorporated into the standard energy minimization framework used in early vision. The energy can then be efficiently minimized using graph cuts, which preserve discontinuities and handle low-texture regions. The resulting algorithm combines the accurate disparity maps that come from graph cuts with the tolerance for intensity changes that comes from mutual information.

Lecture Notes in Computer Science, 2002

In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to... more In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous to the extension from Hidden Markov Models (HMM's) to Factorial HMM's. We present an efficient EM-based algorithm for inference on Factorial MRF's. Our algorithm makes use of the fact that layers are a priori independent, and that layers only interact through the observable image. The algorithm iterates between wide inference, i.e., inference within each layer for the entire set of pixels, and deep inference, i.e., inference through the layers for each single pixel. The efficiency of our method is partly due to the use of graph cuts for binary segmentation, which is part of the wide inference step. We show experimental results for both real and synthetic images.

Journal of X-ray science and technology, 2003

Medical imaging often involves the injection of contrast agents and the subsequent analysis of ti... more Medical imaging often involves the injection of contrast agents and the subsequent analysis of tissue enhancement patterns. Many important types of tissue have characteristic enhancement patterns; for example, in MR mammography, malignancies exhibit a characteristic "wash out" temporal pattern, while in MR angiography, arteries, veins and parenchyma each have their own distinctive temporal signature. In such time resolved image series, there are substantial changes in intensities; however, this change is due primarily to the contrast agent, rather than to motion. As a result, the task of automatically segmenting contrast-enhanced images poses interesting new challenges. In this paper, we propose a new image segmentation algorithm for time resolved image series with contrast enhancement, using a model-based time series analysis of individual pixels. We take an energy minimization approach to ensure spatial coherence. The energy is minimized in an expectation-maximization fa...

Magnetic Resonance in Medicine, 2002

For time-resolved background-subtracted contrast-enhanced magnetic resonance angiography, the bri... more For time-resolved background-subtracted contrast-enhanced magnetic resonance angiography, the bright and sparse arterial signal allows unique identification of contrast bolus arrival in the arteries. This article presents an automatic filtering algorithm using such arterial characterization for selecting arterial phase images and mask images to generate an optimal summary arteriogram. A paired double-blinded comparison demonstrated that this automatic algorithm is as effective as the manual process.