• Journal of Information Processing Systems
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• 제12권1호
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• pp.149-168
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• 2016

The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model in its sequential form is computationally intensive and operates on large data sets. This paper presents another framework to implement the standard version of the AAM model. We suggest a distributed and parallel approach justified by the characteristics of the model and their potentialities. We introduce a schema for the representation of the overall model and we study of operations that can be parallelized. This approach is intended to exploit the benefits build in the area of advanced image processing.

• ETRI Journal
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• 제29권4호
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• pp.489-496
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• 2007

As pervasive computing is widely adopted and reliable networks are becoming more easily accessible, there is a rapidly growing need to develop a mechanism to analyze and evaluate the performance of ubiquitous environments. This paper presents an information processing model which characterizes a ubiquitous environment where a variety of pieces of information need to be exchanged among devices within a system. The proposed model not only provides analytical tools to evaluate the performance of devices, but also makes it possible to identify key factors in designing a ubiquitous environment. For illustrative purposes, a test bed is constructed and the performance of the system is assessed based on the proposed model.

• Journal of Multimedia Information System
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• 제5권4호
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• pp.221-228
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• 2018

Skin-color information is not sufficient for palmprint segmentation in complex scenes, including mobile environments. Traditional active shape model (ASM) combines gray information and shape information, but its performance is not good in complex scenes. An improved ASM method is developed for palmprint segmentation, in which Perux method normalizes the shape of the palm. Then the shape model of the palm is calculated with principal component analysis. Finally, the color likelihood degree is used to replace the gray information for target fitting. The improved ASM method reduces the complexity, while improves the accuracy and robustness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권2호
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• pp.366-385
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• 2013

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.807-825
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• 2020

In recent years, business environments have become more complex; therefore, enterprises must be capable of responding flexibly and agilely. For these purposes, effective enterprise systems service monitoring and early decision making based on the same, emerge as core competency of the enterprise. In addition, enterprise system techniques that filter meaningful data are needed to event processing. However, the existing study related with this is nothing but discovering of service faults by monitoring depending upon API of BPEL engine or middleware, or is nothing but processing of simple events based on low-level events. Accordingly, there would be limitations to provide useful business information. In this study, we present an extended event processing model that enables delivery of more valuable and useful business information through situation detection. Primarily, the event processing architecture in an enterprise system is proposed as a definite approach, and then define an event meta-model suitable for the proposed architecture. Based on the defined model, we propose the syntax and semantics of the elements that make up the event processing language include various and progressive event operators, the rules, complex event pattern, etc. In addition, an event context mechanism is proposed to analyze more delicate events. Finally, the effectiveness and applicability of proposed approach is presented through a case study.

• 정보처리학회지
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• 제15권2호
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• pp.5-14
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• 2008

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권8호
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• pp.299-308
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• 2014

신체 동작, 얼굴 표정과 같이 아주 복잡한 생체 패턴을 인식하고 분류하는 인간의 능력을 모방한 정보처리 컴퓨팅 관련 연구가 최근 다수 등장하고 있다. 특히 컴퓨터비전 분야에서는 인간의 뛰어난 인지 능력 중 상황정보 없이 시각시퀀스에서 동작을 분류하는 기능을 통해 시공간적 패턴 코딩과 빠른 인식 방법을 이해하고자 한다. 본 연구는 비디오 시퀀스상의 동작인식에 생물학적 시각인지과정의 영향을 받은 생체 기반 컴퓨터비전 모델을 제시하였다. 제안 모델은 이미지 시퀀스에서 동작을 검출하고 시각 패턴을 판별하는 데 생체 시각처리과정의 신경망 구조 단계를 반영하였다. 실험을 통해 생체 기반 동작인식 모델이 인간 시각인지 처리의 여러 가지 속성을 고려했을 뿐 아니라 기존 동작인식시스템에 비해 시간 정합성이 뛰어나며 시간 변화에 강건한 분류 능력을 보임을 알 수 있다. 제안 모델은 지능형 로봇 에이전트와 같은 생체 기반 시각정보처리 시스템 구축에 기여할 수 있다.

• Journal of Computing Science and Engineering
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• 제8권1호
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• pp.17-24
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• 2014

In this paper, we propose a new implementation of a failure detector. The implementation uses a dual model of heartbeat and interaction. First, the heartbeat model is adopted to shorten the detection time, if the detection process does not receive the heartbeat message in the expected time. The interaction model is then used to check the process further. The expected time is calculated using the exponential smoothing method. Exponential smoothing can be used to estimate the next arrival time not only in the random data, but also in the data of linear trends. It is proven that the new detector in the paper can eventually be a perfect detector.

• 디자인학연구
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• 제16권1호
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• pp.289-296
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• 2003

본 논고는 제품디자인 방법에서의 정보수집과 조직화 과정에 대한 정보처리모델을 개념적으로 연구한 것이다 과거의 디자인은 디자이너가 직접 손으로 소재를 다듬어 제품을 만들었으나, 소재가 정보로 전환된 오늘날의 제품디자인은 본질적으로 정보의 수집과 조직화 과정에 의해 이루어진다고 볼 수 있다. 제품디자인이 정보 처리과정이라고 한다면, 그것은 정보 이론의 양적인 변환이 아니라, 주로 정보의 질적인 변환을 의미한다. 본 연구의 초점은 제품디자인에서 소재가 아닌, 용도를 지향할 때 다루어지는 대상을 정보로 전환, 처리되는 모델을 개념화하는데 있다. 기존에는 합리적인 문제해결을 위한 제품디자인 방법의 논의는 <분석-종합-평가>의 프로세스 모델을 기본으로 한 정량적, 정성적, 유기적 방법들과 수단으로서의 모델링에 관한 주로 형식론적인 것이었다면, 제품디자인에서 정보처리방법은 물질을 형태화하기에 앞서, 대상물의 소재를 추상화, 구조화하여 디자인 지향의 정보로 모델링해야 한다. 디지털 환경의 기반 하에서 제품디자인의 성패는 과거 소재에 직접 가공하던 것과는 달리, 무엇을 어떻게 해야 할 것인지 결정하기 위해 정보를 어떻게 다루느냐에 달려 있다.

• Journal of Information Processing Systems
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• 제5권1호
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• pp.11-18
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• 2009

As well as providing various APIs for the development of inference engines and storage models, Jena is widely used in the development of systems or tools related with Web ontology management. However, Jena still has several problems with regard to the development of real applications, one of the most important being that its query processing performance is unacceptable. This paper proposes a storage model to improve the query processing performance of the original Jena storage. The proposed storage model semantically classifies OWL elements, and stores an ontology in separately classified tables according to the classification. In particular, the hierarchical knowledge is managed, which can make the processing performance of inferable queries enhanced and stores information. It enhances the query processing performance by using hierarchical knowledge. For this paper an experimental evaluation was conducted, the results of which showed that the proposed storage model provides a improved performance compared with Jena.