• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.79-82
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• 2012

컴퓨터 비전에서 영상 매칭 기술은 다양한 분야에 응용될 수 있는 기초적인 기술 중에 하나이다. 강인한 영상 매칭을 위해서는 정확하고 독특한 특징점을 검출하는 과정이 중요하다. 기존의 SIFT나 SURF 등 영상 매칭 알고리즘은 등방성 가우시안 필터링을 사용한 스케일 공간을 생성하여 특징점을 검출한다. 이러한 기존의 특징점 검출 방식은 스케일 공간에서 영상의 경계선을 모호하게 만들어 정확한 특징점 검출을 어렵게 만들고 영상 매칭의 성능을 떨어뜨리는 문제점을 가지고 있다. 본 논문에서는 SIFT 알고리즘의 강인한 특징점 검출을 위하여 양방향 필터링을 사용하여 스케일 공간 생성을 제안한다. 이러한 스케일 공간 생성 방식은 스케일 공간에서 영상의 경계선을 보존해 줌으로서 강인한 특징점 검출을 가능하게 하여 영상 매칭 성능을 향상시킨다. 특히 왜곡이 존재하는 영상들의 매칭에서 제안하는 특징점 검출 방법이 적용된 SIFT 알고리즘은 기존의 SIFT 알고리즘보다 우수한 영상 매칭 결과를 보여준다.

• Journal of the Korean Geographical Society
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• v.42 no.5
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• pp.691-709
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• 2007

This paper investigates the social and political construction of geographical scale in conjunction with Korean housing politics. Recently, attention has been drawn to the issue of the social and political construction of geographical scale. Spatial scales have increasingly been regarded as socially constructed and politically contested rather than ontologically pregiven or fixed. The scale literature has paid attention to how different spatial scales can be used or articulated in social movements, with an emphasis on 'up-scaling' and 'scales of activism' rather than 'down-scaling' and 'scales of regulation.' Furthermore, the scale literature has focused on the aspect of empowerment. However, it is worthwhile to examine how scale-especially 'down-scaling' and 'scales of regulation'-can be used not only for marginalizing or excluding unprivileged social groups, but also for controlling the (re)production of space, including housing space. Under a regulatory regime, the Korean central government gained more control over the (re)production of housing space at geographical multi-scales by means of 'jumping scales,' specifically 'down-scaling.' The Korean central government has increasingly obtained the capacity to 'jump scales' by using not only multiscalar strategies for housing developments, but also taking advantage of various scales of institutional networking among the central and local governments, quasi-governmental institutions, and Chaebols, across the state. Traditionally, scale has been regarded as an analytical spatial unit or category. However, scale can be seen as means of inclusion(and exclusion) and legitimation. Choosing institutions to include or exclude cannot be separated from the choices and range of spatial scale, and is closely connected to 'scale spatiality of politics.' Facilitating different forms of 'scales of regulation,' the Korean central government included Chaebols and upper- and middle-income groups for the legitimization of housing projects, but excluded local-scale grassroots organizations and unprivileged social groups as decision-makers.

• Journal of KIISE
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• v.42 no.1
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• pp.93-96
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• 2015

The SIFT method is well-known for robustness against various image transformations, and is widely used for image retrieval and matching. The SIFT method extracts keypoints using scale space analysis, which is different from conventional keypoint detection methods that depend only on the image space. The SIFT method has also been extended to use higher-order scale space derivatives for increasing the number of keypoints detected. Such detection of additional keypoints detected was shown to provide performance gain in image retrieval experiments. Herein, a sigma based normalization method for keypoint detection is introduced using higher-order scale space derivatives.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1326-1329
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• 2015

최근 들어 공간 지식을 활용한 다양한 서비스들이 개발됨에 따라, 공간 객체들 간의 정성적 공간 관계를 표현한 정성 공간 지식의 수요가 크게 늘어나고 있다. 공간 객체 각각의 세부 정보를 담은 대용량의 공간 데이터들은 개방화가 점차 확대되고 있으나, 공간 객체들 간의 정성적 관계를 표현한 정성 공간 지식은 상대적으로 확보하기 어려운 실정이다. 본 논문에서는 하둡 맵리듀스 병렬 분산 컴퓨터 환경을 이용해, 대용량의 공간 데이터로부터 공간 객체들 간의 위상 관계와 방향 관계를 나타내는 정성 공간 지식을 자동으로 추출하는 공간 지식 추출기를 제안한다. 본 논문에서 제안하는 대용량의 공간 지식 추출기는 맵리듀스 프레임워크를 기반으로 R-트리 색인과 범위 질의들을 효과적으로 이용함으로써, 웹 스케일 수준의 정성 공간 지식을 매우 효율적으로 추출해낸다. Open Street Map (OSM) 공개 데이터를 이용한 성능 분석 실험을 통해, 본 논문에서 제안하는 대용량 공간 지식 추출기의 높은 성능을 확인할 수 있었다.

• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.123-139
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• 2015

This paper attempts to complement the methodological and conceptual lack of spatial thinking in Korean women's movement research and to facilitate further discussion on this field of research, by drawing on recent academic discussion on scale developed particularly among the Western critical and feminist geographers. The purposes of the paper are following. First, it addresses the need to utilize the concept of scale in women's movement research. Numerous spatial metaphors often proliferated with indiscretion in the feminist approach have rather tended to hinder fully understanding the spatiality of social movements. In order to examine the spatiality of social movements as both conceptual tool and praxis, not merely as metaphor, the paper incorporates main issues in recent scale discourses with particular attention to the debate between Marston and Brenner, and explores their implications for women's movement research in Korea. Second, it emphasizes the multi-scalar approach by highlighting the role of micro-scale, the less studied side in social movement literature. The public and the private divide, the long time battle ground in feminist research, is often intermingled with the hierarchical scalar understanding which considers the global as more powerful and important than the local. The reproductive realm, however, is indispensably related to production and political economic realm. The paper explores the very site where both the public/private divide and the hierarchical scalar understanding can be dismantled. It is the site where the private becomes public and the local becomes the global (and vice versa). Drawing on a brief example of an anti-FTA movement of women with strollers in Korea, it examines the way the multi-scalar approach advances the understanding of Korean women's movement.

• Journal of the Korean Geographical Society
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• v.42 no.5
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• pp.808-834
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• 2007

This study attempts to elucidate manifold dimensions of gendered accessibility experiences. How gender roles(household responsibilities) differentiate accessibility experiences between women and men is explored through the comparison of married dual-earner couples' parental status, using the US Portland activity-travel diary dataset with GIS-based geocomputation results of(time-geography based) space-time accessibility. First, this study shows how gender division of labor within the household still permeates current society, despite the widespread belief of the social change toward a gender-egalitarian society. Then, the study pays special attention to the way gender roles structure individual accessibility experiences of women and men differently, and, in turn, the way such accessibility experiences take a form of gendered spatiality. Gendered spatiality is examined through the analysis of accessibility space as well as activity space in order to ascertain women's home-attached and spatially entrapped characteristics. More household responsibilities throughout a day and, even more, the time constraint of picking up children at the daycare centers after work lead women's possible activity space to be more home-centered. The analysis of the spatio-temporal context of accessibility space makes gendered spatiality visible. However, the findings suggest that behavioral outcomes should be understood with an explicit awareness of constraints individuals face. It is because the revealed activity spaces can be not only an outcome of constraint but also an outcome of choice. Behavioral outcomes should not be treated as a straightforward expression of the level of constraints. It is problematic to expect that behavioral outcomes directly mirror the level of constraints. It is also problematic to suppose that the level of constraints can be straightforwardly elicited from revealed behavioral outcomes.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.151-154
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• 2005

본 논문에서는 스케일러블 멀티미디어 콘텐츠에 대한 조건적 접근제어가 가능한 암호화 방법을 제안한다. 현재 표준화가 진행중인 스케일러블 비디오 코딩방법인 JSVM(Joint Scalable Video Model)은 부호화한 동영상에 대해 공간, 시간, 품질의 스케일러빌리티(Scalability)를 지원하는데, 각 스케일러 빌리티를 고려한 조건적인 접근제어기술은 스케일러빌리티에 따라 사용자를 제한해야 하는 경우를 위해 필수적인 기술이다. 제안하는 방법은 공간, 시간, 품질의 세가지 스케일러빌리티를 지원하도록 부호화(Encoding)후 구성되는 NAL(Network Abstract Layer)을 지원하는 스케일러빌리티에 따라 구분하고, 구분된 NAL 의 종류에 따라 암호화 key 를 다르게 제공하는 방법을 통해 사용자의 접근제어 수준에 맞게 암호화 key 를 조합하는 방법을 적용하였다. 실험 결과 제안한 방법은 JSVM 에서 공간, 시간, 품질의 스케일러빌리티가 보장되고, 이때 생성되는 Key 의 조합으로 조건적 접근제어(Conditional access control)가 가능함을 확인하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.1-6
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• 2018

In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.1-3
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• 2022

최근 기존의 영상 압축 파이프라인 대신 신경망의 종단 간 학습을 통해 압축을 수행하는 알고리즘의 연구가 활발히 진행되고 있다. 본 논문은 종단 간 학습 기반 공간적 스케일러블 압축 기술을 제안한다. 보다 구체적으로 본 논문은 신경망의 각 계층에서 하위 계층의 학습된 특징 (feature)을 융합하여 상위 계층으로 전달하는 다중 스케일 특징 융합 (multi-scale feature fusion) 모듈을 도입해 상위 계층이 더욱 풍부한 특징 정보를 학습하고 계층 사이의 특징 중복성을 더욱 잘 제거할 수 있도록 한다. 기존 방법 대비 향상 계층(enhancement layer)에서 1.37%의 BD-rate가 향상된 결과를 볼 수 있다.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.