김정호 교수

본 연구에서는 Z-R 관계식의 매개변수를 안정적인 값으로 실시간 예측하고자 확장 칼만 필터기법을 적용하였다. 이를 위해 Z-R 관계식의 비선형을 고려하여 확장 칼만필터로 매개변수 결정모형을 구축하였다. 상태-공간모형은Adamowski and Muir (1989)의 연구를 기반으로 구축하였다. 상태-공간 모형의 상태변수는 Z-R 관계식의 두 매개변수로 설정하였다. 결과적으로 칼만이득과 상태변수가 발산하지 않는 안정적인 모형을 구축하였다. 주목할 점으로는 기존 방법으로 추정된 과대 혹은 과소한 매개변수가 필터링 되어 일부 제거되었다는 것이다. 부적절한 매개변수의 적용은 물리적으로 비현실적인 강우강도 추정 결과를 불러일으키는 원인이기 때문에 이러한 결과는 정량적 강수량 추정측면에서 효과가 크다고 할 수 있다. 또한 확장 칼만 필터로 예측한 매개변수로 레이더 강우를 추정한 결과, 편의보정계수가 1.0에 근사하게 나타나 편의보정과정 없이도 지상 강우강도와의 평균적인 차이는 근소한 것으로 나타

Performance interference between QoS and best-effort applications is getting more aggravated as data-intensive applications are rapidly and widely spreading in recently emerging computing systems. While the completely fair scheduler (CFS) of the Linux kernel has been extensively used to support performance isolation in a multitasking environment, it falls short of addressing memory-related interference due to memory access contention and insufficient cache coverage. Though quite a few memory-awa

Software extensibility, the capability of adding new functions to a software system, is established based on software architecture. Therefore, developers need to evaluate the capability when designing software architecture. To support the evaluation, researchers have proposed metrics based on quality models or scenarios. However, those metrics are vague or subjective, depending on specific systems and evaluators. We propose the extensibility metric for software architecture (EMSA), which represe

With the advent of high-performance multicore processors that operate under a limited power budget, dedicated low-end microprocessors with different levels of criticality are rapidly consolidated into a mixed-criticality system. One of the major challenges in designing such a mixed-criticality system is to tightly control the amount of resource contention for a critical application by effectively limiting its performance interference incurred due to sharing resources with non-critical tasks. In

Recently, many vision-based robotic applications such as visual SLAM (Simultaneous Localization And Mapping) and autonomous navigation have achieved good performance using visual features. In these applications, robust feature tracking plays an important role, e.g., in scene recognition for autonomous navigation and in data association for visual SLAM. In this paper, we propose a hierarchical outlier detection algorithm for robust feature tracking; the algorithm uses a simple window-based correl

This paper addresses a navigation method which copes with dynamic environments, e.g. objects moving in the environment and environment changes. Because many vision-based navigation methods mainly focus on finding consistent corresponding parts with one of the database images, dynamic environments can cause the failure of autonomous navigation due to visual occlusion. To solve these problems, we propose a motion-based navigation method in contrast with appearance-based approaches. We also solve t

This paper describes the development of integrated head and eye tracker system. Head tracker is performed vision based and it has 7 mm error in 300 mm translation. The epipolar method and point matching are used for determining a position of head and rotational degree. High brightness LEDs are installed on helmet and the installed pattern is very important to match the points of stereo system. Eye tracker also uses LED for constant illumination. A Position of gazed object (3 m distance) is deter

Vision-based robotic applications such as Simultaneous Localization and Mapping (SLAM), global localization, and autonomous navigation have suffered from problems related to dynamic environments involving moving objects and kidnapping. One of the possible solutions to these problems is to establish robust correspondences when obtaining images from static scenes. Therefore we propose an efficient technique for determining correspondences to recover the current camera pose; in the proposed method,

Recently, public interest in the blockchain technology has surged and various applications based on the technology have emerged. However, there has been little study on architectural evaluations of popular block chain platforms that can help the developers choose an appropriate architecture matching their needs. In this paper, we reconstruct and evaluate the architecture of Hyperledger and Ethereum, which are representative open source platforms for blockchain. The evaluation results indicate th

One fundamental problem of object tracking is the convergence of estimates to local maxima not corresponding to target objects. To mitigate this problem, constructing a good posterior distribution of the target state is important. In this letter, we propose a robust tracking approach by building a new posterior distribution model from multiple independent estimates of a target state. For each candidate of the target state, we compute a confidence score based on its spatial consistency with other

Object detection in real images or videos is challenging because the shapes and sizes of objects vary significantly according to their poses, camera viewing direction, and partial occlusion. Previous detection methods employ sliding-window-based schemes that scan windows across an image, requiring many differently shaped windows to capture shape and size variation. In order to solve this problem, we propose an object detection method using hierarchical graph-based segmentation: color-consistent

One of the most important problems in visual tracking is how to incrementally update the appearance model because the appearance of a target object can be easily changed with time when the target is a deformable object or it is moving under varying illumination conditions. To solve these problems, we present a Rao-Blackwellized particle filter (RBPF)-based object tracking algorithm with the adaptive appearance model represented by a Gaussian mixture model (or a mixture of Gaussians model) becaus