• 제목/요약/키워드: background prior

검색결과 660건 처리시간 0.028초

Background Prior-based Salient Object Detection via Adaptive Figure-Ground Classification

  • Zhou, Jingbo;Zhai, Jiyou;Ren, Yongfeng;Lu, Ali
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권3호
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    • pp.1264-1286
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    • 2018
  • In this paper, a novel background prior-based salient object detection framework is proposed to deal with images those are more complicated. We take the superpixels located in four borders into consideration and exploit a mechanism based on image boundary information to remove the foreground noises, which are used to form the background prior. Afterward, an initial foreground prior is obtained by selecting superpixels that are the most dissimilar to the background prior. To determine the regions of foreground and background based on the prior of them, a threshold is needed in this process. According to a fixed threshold, the remaining superpixels are iteratively assigned based on their proximity to the foreground or background prior. As the threshold changes, different foreground priors generate multiple different partitions that are assigned a likelihood of being foreground. Last, all segments are combined into a saliency map based on the idea of similarity voting. Experiments on five benchmark databases demonstrate the proposed method performs well when it compares with the state-of-the-art methods in terms of accuracy and robustness.

창의적 아이디어 산출에 대한 배경지식과 사례의 영향 (The Effects of Background Knowledge and Prior-Examples in Creative Problem Solving)

  • 이정모;정재학
    • 인지과학
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    • 제13권2호
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    • pp.47-59
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    • 2002
  • 본 연구에서는 창의적 아이디어 산출에 대한 선행정보로서 배경지식과 사전에 제시되는 사례들이 어떤 영향을 미치는지를 알아보기 위해 수행되었다. 실험 1에서는 사례의 일상성이 창의적 아이디어 산출에 관련이 있는지를 알아보았다. 실험 2에서는 배경지식과 사례의 독특성 정도가 창의적 아이디어 산출에 미치는 영향에 대해 살펴보았다 실험 3에서는 배경지식과 사례의 복합적 관계가 창의적 아이디어 산출에 어떤 영향을 미치는지를 알아보았다. 본 연구에서는 아이디어 산출과정에서 사례와 배경지식 모두에서 일상적 경우보다 비일상적 경우가 창의적 문제해결에서 긍정적 영향을 미친다는 결과를 얻었다. 또한 일상적인 사례를 제공받은 조건에서도 배경지식의 속성을 다양하게 제공받거나 비 일상적인 배경지식(문제와 직접관련성이 없는 내용)을 제공받는 경우 창의적인 문제해결에서 긍정적인 결과를 얻을 수 있었다. 이는 배경지식과 사례들이 서로 상호작용 하여 선행정보로서 창의적 문제해결에 영향을 미침을 시사한다.

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움직이는 카메라에 의한 변화하는 환경하의 강인한 배경 획득 및 유동체 검출 (Robust background acquisition and moving object detection from dynamic scene caused by a moving camera)

  • 김태호;조강현
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (C)
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    • pp.477-481
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    • 2007
  • A background is a part where do not vary too much or frequently change in an image sequence. Using this assumption, it is presented a background acquisition algorithm for not only static but also dynamic view in this paper. For generating background, we detect a region, where has high correlation rate compared within selected region in the prior pyramid image, from the searching region in the current image. Between a detected region in the current image and a selected region in the prior image, we calculate movement vector for each regions in time sequence. After we calculate whole movement vectors for two successive images, vector histogram is used to determine the camera movement. The vector which has the highest density in the histogram is determined a camera movement. Using determined camera movement, we classify clusters based on pixel intensities which pixels are matched with prior pixels following camera movement. Finally we eliminate clusters which have lower weight than threshold, and combine remained clusters for each pixel to generate multiple background clusters. Experimental results show that we can automatically detect background whether camera move or not.

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SEGMENTATION WITH SHAPE PRIOR USING GLOBAL AND LOCAL IMAGE FITTING ENERGY

  • Terbish, Dultuya;Kang, Myungjoo
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제18권3호
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    • pp.225-244
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    • 2014
  • In this work, we discuss segmentation algorithms based on the level set method that incorporates shape prior knowledge. Fundamental segmentation models fail to segment desirable objects from a background when the objects are occluded by others or missing parts of their whole. To overcome these difficulties, we incorporate shape prior knowledge into a new segmentation energy that, uses global and local image information to construct the energy functional. This method improves upon other methods found in the literature and segments images with intensity inhomogeneity, even when images have missing or misleading information due to occlusions, noise, or low-contrast. We consider the case when the shape prior is placed exactly at the locations of the desired objects and the case when the shape prior is placed at arbitrary locations. We test our methods on various images and compare them to other existing methods. Experimental results show that our methods are not only accurate and computationally efficient, but faster than existing methods as well.

EDXRF 스펙트럼을 위한 효율적인 배경 모델링과 보정 방법 (An Efficient Background Modeling and Correction Method for EDXRF Spectra)

  • 박동선;자가디산 수카니아;진문용;윤숙
    • 전자공학회논문지
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    • 제50권8호
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    • pp.238-244
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    • 2013
  • 에너지 분산형 X-선 형광(EDXRF) 분석에서 X-선 스펙트럼에 존재하는 컨티넘(continuum)의 추정 및 제거는 필수적이다. 이를 위해 일반적으로 사용되는 알고리즘들은 많은 주의가 필요하며 복잡하다. 보통 이 알고리즘들은 제약적이거나 컨티넘의 데이터나 모양에 대한 가설을 필요로 한다. 본 논문에서는 제안된 에너지 분산형 X-선 형광 스펙트럼을 위한 효율적인 배경(background) 보정 방법은 배경 모델링과 배경 보정으로 구성된다. 이 방법은 스펙트럼에서 백그라운드영역과 피크영역을 구분하는 기본 개념을 기반으로 하며 성능향상을 위하여 SNIP알고리즘을 사용한다. 스펙트럼으로부터 배경에 속하는 점들을 획득한 후 이를 기반으로 곡선 근사화를 통해 배경을 모델링한다. 이후 획득된 배경 모델을 원 스펙트럼에서 뺌으로써 배경이 보정된 스펙트럼을 얻는다. 제안된 방법은 상대적으로 적은 사전 지식을 요구하면서 기존의 몇몇 방법들에 비해 우수한 결과를 보여주었다.

Real-Time Vehicle Detector with Dynamic Segmentation and Rule-based Tracking Reasoning for Complex Traffic Conditions

  • Wu, Bing-Fei;Juang, Jhy-Hong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권12호
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    • pp.2355-2373
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    • 2011
  • Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

Bayesian MCMC를 이용한 저수량 점 빈도분석: I. 이론적 배경과 사전분포의 구축 (At-site Low Flow Frequency Analysis Using Bayesian MCMC: I. Theoretical Background and Construction of Prior Distribution)

  • 김상욱;이길성
    • 한국수자원학회논문집
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    • 제41권1호
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    • pp.35-47
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    • 2008
  • 저수분석(low flow analysis)은 수자원공학에서 중요한 분야 중 하나이며, 특히 저수량 빈도분석(low flow frequency analysis)의 결과는 저수(貯水)용량의 설계, 물 수급계획, 오염원의 배치 및 관개와 생태계의 보존을 위한 수량과 수질의 관리에 중요하게 사용된다. 그러므로 본 연구에서는 저수량 빈도분석을 위한 점 빈도분석을 수행하였으며, 특히 빈도분석에 있어서의 불확실성을 탐색하기 위하여 Bayesian 방법을 적용하고 그 결과를 기존에 사용되던 불확실성 탐색방법과 비교하였다. 본 논문의Ⅰ편에서는 Bayesian 방법 중 사전분포(prior distribution)와 우도함수(likelihood function)의 복잡성에 상관없이 계산이 가능한 Bayesian MCMC(Bayesian Markov Chain Monte Carlo) 방법과 Metropolis-Hastings 알고리즘을 사용하기 위한 여러 과정의 이론적 배경과 Bayesian 방법에서 가장 중요한 요소인 사전분포를 구축하고 이를 비교 및 평가하였다. 고려된 사전분포는 자료에 기반하지 않은 사전분포와 자료에 기반한 사전분포로써 두 사전분포를 이용하여 Metropolis-Hastings 알고리즘을 수행하고 그 결과를 비교하여 저수량 빈도분석에 합리적인 사전분포를 선정하였다. 또한 알고리즘의 수행과정에서 필요한 제안분포(proposal distribution)를 적용하여 그에 따른 알고리즘의 효율성을 채택률(acceptance rate)을 산정하여 검증해 보았다. 사전분포의 분석 결과, 자료에 기반한 사전분포가 자료에 기반하지 않은 사전분포보다 정확성 및 불확실성의 표현에 있어서 우수한 결과를 제시하는 것을 확인할 수 있었고, 채택률을 이용한 알고리즘의 효용성 역시 기존 연구자들이 제시하였던 만족스러운 범위를 가지는 것을 알 수 있었다. 최종적으로 선정된 사전분포는 본 연구의 II편에서 Bayesian MCMC방법의 사전분포로 이용되었으며, 그 결과를 기존 불확실성의 추정방법의 하나인 2차 근사식을 이용한 최우추정(maximum likelihood estimation)방법의 결과와 비교하였다.

들기/내리기 작업 시 소음과 배경음악이 몸통근육 피로도에 미치는 영향 (The Effect of Noise and Background Music on the Trunk Muscle Fatigue during Dynamic Lifting and Lowering Tasks)

  • 김정룡;신현주;이인재
    • 대한인간공학회지
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    • 제27권3호
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    • pp.15-22
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    • 2008
  • The purpose of this study was to define the effects of noise and background music on the trunk muscle fatigue during dynamic lifting and lowering tasks. Six healthy male subjects with no prior history of low back disorders participated in this study. The participants were exposed to two levels of background noise such as 40dB noise and 90dB noise and three levels of background music such as no music, slow music, and fast music. Six different combinations of background noise and background music were played while the participants were performing the lifting task at 15% level of Maximum Voluntary Contraction. Electromyography signals from six muscles were collected and fatigue levels were analyzed quantitatively. In results, the 90dB noise increased trunk muscle fatigue and slowed down the recovery. The trunk muscle fatigue was the lowest when the fast music was played for as background. After recovery, the 90dB noise increased trunk muscle fatigue. The trunk muscle fatigue was the lowest when the slow music was played for as background. The results can be useful to manage the cumulative fatigue of trunk muscles due to background noise and music during repetitive lifting and lowering tasks in industry.

Salient Object Detection via Multiple Random Walks

  • Zhai, Jiyou;Zhou, Jingbo;Ren, Yongfeng;Wang, Zhijian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권4호
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    • pp.1712-1731
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    • 2016
  • In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.

건축 거푸집 설계 응력산정 프로그램 개발에 관한 기초적 연구 (Programming for the Structural Analysis of Form Structure)

  • 손기상
    • 한국안전학회지
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    • 제8권1호
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    • pp.21-28
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    • 1993
  • Occupational Safety & Health Code requires to calculate Design Load and stress for the approval within thirty working days prior to initiating each construction site work This study is to develop an easy and useful program that each safety manager. Controller or engineers are able to make output for the above mentioned form structure analyses without knowledge or engineering background of it. Therefore. three, randomly selected. different major student and engineers verified if they could make output. really without the engineering background. And then some deficiencies are corrected after finding those from the program operation.

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