비대면 연극치료 프로그램 개발에 관한 연구 – 『성냥팔이 소녀』이야기를 중점으로

정소라 한국연극예술치료학회 2022 연극예술치료연구 Vol.- No.17

Drama therapists in the COVID-19 are experienced non-face-to-face drama therapy, confirmed the possibility at a different point from face-to-face drama therapy. Research on non-face-to-face drama therapy is insufficient and studies on various topics are needed, but the researcher paid attention to program development, case studies, and comparative studies on face-to-face and non-face-to-face methods. This is essential for the development and expansion of non-face-to-face drama therapy. Therefore, the purpose of this study is to select a story suitable for non-face-to-face drama therapy and apply this program to the same subject in a face-to-face and non-face-to-face manner to examine the therapeutic effects that vary depending on the method and to reveal the therapeutic factors of non-face-to-face drama therapy. In the story of The Little Match-Seller the main character's fantasy scene experience is the most important element of the story, and in a non-face-to-face drama treatment environment, it can be experienced in a more special form. The drama treatment program using the story of The Little Match-Seller was piloted to the same subject in three ways: face-to-face, ZOOM, and video, and the therapeutic factors were identified through surveys, interviews, and literature research. As a result of the study, the first therapeutic factor that should be recognized as important in non-face-to-face drama therapy is interaction. Based on the close interaction between digital media, therapists, and participants, immediate intervention due to the participant's dynamics was possible, so it could have a therapeutic effect. The second therapeutic factor is imaginary therapeutic power. In non-face-to-face drama therapy, digital media characteristics, personal costumes, space, and video language can be used to infinitely develop more personal and original imagination. In other words, the fundamental therapeutic factor of non-face-to-face drama therapy is interaction, and the point where face-to-face methods and differentiation are possible can be personal, original, and infinite imagination. 코로나 시대 연극 치료사들은 비대면 연극치료를 경험했고 대면 연극치료와는 다른 지점에서 그 가능성을 확인하였다. 비대면 연극치료 연구는 미비한 실정이며 다양한 주제의 연구가 필요하지만 연구자는 그 중에서도 프로그램 개발과 사례 연구, 대면과 비대면 방식의 비교 연구에 주목하였다. 이는 비대면 연극치료의 발전과 확장에 필수적이다. 따라서 본 연구의 목적은 비대면 연극치료에 적합한 이야기를 선정하여 이 프로그램을 대면․비대면 방식으로 동일 대상에게 적용하여 방식에 따라 다르게 나타나는 치료적 효과를 살펴보고 비대면 연극치료의 치료적 요인을 밝히는 데 있다. 『성냥팔이 소녀』이야기에서 주인공의 환상 장면 경험은 이야기의 가장 중요한 요소이며 비대면 연극치료 환경에서는 보다 특수한 형태로 이를 경험할 수 있다. 『성냥팔이 소녀』이야기를 활용한 연극치료 프로그램을 대면․ZOOM․동영상 3가지 방식으로 동일 대상에게 시범 수업하였고 설문 조사와 인터뷰, 문헌 연구를 통해 치료적 요인을 밝히고자 하였다. 연구 결과 비대면 연극치료에서 중요하게 인식해야 하는 첫 번째 치료적 요인은 상호 작용성이다. 디지털 매체, 치료사, 참여자 사이의 긴밀한 상호 작용을 토대로 참여자의 역동에 따른 즉각적인 개입이 가능했기 때문에 치료적 효과가 나타났다. 두 번째 치료적 요인은 상상의 치료적 힘이다. 비대면 연극치료에서는 디지털 매체 특성과 개인 의상 및 공간, 영상 언어를 활용하여 보다 개인적이고 독창적인 상상력을 무한하게 펼쳐낼 수 있다. 다시 말해 비대면 연극치료의 근본적인 치료적 요인은 상호 작용성이며 대면 방식과 차별화가 가능한 지점은 개인적이고 독창적이며 무한한 상상력을 펼쳐낼 수 있다는 것이다.

Real-time Face Tracker using Ellipse Fitting and Color Look-up Table in Irregular Illumination

Hyun Seok Hong,Dong Hyun Yoo,Myung Jin Chung 한국과학기술원 인간친화 복지 로봇 시스템 연구센터 2002 International Journal of Assistive Robotics and Me Vol.3 No.4

  In this paper, a real-time face tracker for a service robot is introduced. Color information is very useful for detecting human skin color, and makes it possible to reduce the searching area and searching time. We use the Hand S values of the HSI color model to detect human skin color. To cope with illumination change during tracking in realtime, we use a color look-up-table, which is made up in all illumination change. The region grouping process is applied to a color segmented image to find face candidate blobs. At each frame, we apply pattern matching to every face candidate blob using normalized correlation coefficients to verify the presence of a face pattern. Each face candidate blob is fitted by an ellipse, and its major and minor axes are computed. The direction of the major axis determines the planar rotation angle of a face. The length of the minor axis determines the size of the face template. This method makes the face detection fast and detects the 2D rotation angle. To achieve high reliability of face detection, we use light condition compensation and histogram equalization as a preprocess of pattern matching. This real-time face tracker is efficient for human-robot interaction, e.g. face recognition and eye-gaze tracking systems.

Changes in Effective Connectivity According to Working Memory Load: An fMRI Study of Face and Location Working Memory Tasks

JoonShik Kim,WiHoon Jung,DoHyung Kang,JiYoung Park,JoonHwan Jang,JungSeok Choi,ChiHoon Choi,Jejoong Kim,JunSoo Kwon 대한신경정신의학회 2012 PSYCHIATRY INVESTIGATION Vol.9 No.3

Objective-The functional strategic mechanisms in the brain during performing visuospatial working memory tasks, especially tasks with heavy load, are controversial. We conducted the functional magnetic resonance imaging (fMRI) while sixteen subjects were performing face- and location-matching n-back tasks to examine causal relations within the frontoparietal networks. Methods-We applied a sophisticated method, the structural equation modeling (SEM), to the fMRI data. The imaging data were analyzed by extracting the task-related eigenseries using the principal component analysis (PCA) and then by applying a form of data-driven model called the automated search method. Results-The SEM analyses revealed a functional shift of network connectivity from the right to the left hemisphere with increasing load in the face-matching n-back tasks while the location-matching tasks required bilateral activation. In the locating matching n-back tasks, a pattern of parallel processing was observed in the left phonological loop and the right inferior parietal regions. Furthermore, object working memory-related activities in the left hemisphere reliably contributed to performance of both the face- and location-matching 2-back tasks. Conclusion-Our results are consistent with previous reports in terms of demonstrating parallel and distributed information processing during performing working memory tasks with heavy loads. Our results additionally suggest a dynamic shift between the fast imagery circuit (right hemisphere) and the stable verbal circuit (left hemisphere), depending on task load.

Retrieve CAD Model Based on Face Matching Sequence

Gao Xue-Yao,Li Hui-Nan,Hu Ru,Zhang Chun-Xiang 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.3

A new model retrieval method based on face matching sequence is proposed in this paper. Attribute adjacent graph is used to describe two faces’ geometry similarity and topological relationship in CAD model. According to the difference of edge numbers, similarities between two models’ faces are computed and face similarity matrix is constructed. Ant colony algorithm (ACA) is applied to obtain an optimal sequence of matching faces between two models. Accumulate similarity values of optimal matching faces to calculate two models’ similarity. Experimental results show that this method can evaluate two CAD models’ shape difference effectively.

실시간 얼굴 방향성 추정을 위한 효율적인 얼굴 특성 검출과 추적의 결합방법

김웅기 ( Woonggi Kim ),전준철 ( Junchul Chun ) 한국인터넷정보학회 2013 인터넷정보학회논문지 Vol.14 No.6

본 논문에서는 실시간으로 입력되는 비디오 영상으로부터 사용자의 얼굴 방향을 효율적으로 추정하는 새로운 방법을 제안하였다. 이를 위하여 입력 영상으로부터 외부조명의 변화에 덜 민감한 Haar-like 특성을 이용하여 얼굴영역의 검출을 수행하고 검출 된 얼굴영역 내에서 양쪽 눈, 코, 입 등의 주요 특성을 검출한다. 이 후 실시간으로 매 프레임마다 광류를 이용해 검출된 특징 점을 추적하게 되며, 추적된 특징 점을 이용해 얼굴의 방향성 추정한다. 일반적으로 광류를 이용한 특징 추적에서 발생할 수 있는 특징점의 좌표가 유실되어 잘못된 특징점을 추적하게 되는 상황을 방지하기 위하여 검출된 특징점의 템플릿 매칭(template matching)을 사용해 추적중인 특징점의 유효성을 실시간 판단하고, 그 결과에 따라 얼굴 특징 점들을 다시 검출하거나, 추적을 지속하여 얼굴의 방향성을 추정을 가능하게 한다. 탬플릿 매칭은 특징검출 단계에서 추출된 좌우 눈, 코끝 그리고 입의 위치 등 4가지 정보를 저장한 후 얼굴포즈 측정에 있어 광류에의해 추적중인 해당 특징점들 간의 유사도를 비교하여 유사도가 임계치를 벗어 날 경우 새로이 특징점을 찾아내는 작업을 수행하여 정보를 갱신한다. 제안된 방법을 통해 얼굴의 특성 추출을 위한 특성 검출과정과 검출된 특징을 지속적으로 보완하는 추적과정을 자동적으로 상호 결합하여 안정적으로 실시간에 얼굴 방향성 추정 할 수 있었다. 실험을 통하여 제안된 방법이 효과적으로 얼굴의 포즈를 측정할 수 있음을 입증하였다. In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

장애인 대상 설문조사의 조사 방법에 따른 비표본오차 비교 : 대면조사와 비대면조사 방식의 비교를 중심으로

임예직 통계청 2023 통계연구 Vol.28 No.1

The purpose of this study is to verify the statistical differences in response to non-face-to-face surveys introduced in accordance with the changing social environment such as COVID-19 and to find an appropriate survey method for Persons with disabilities(PWDs). To this end, propensity score matching and regression analysis were conducted based on the results of the responses of 3,695 people who responded to the 2021 PSED(Panel Survey Employment for PWDs) 2nd wave, and statistically confirmed whether there was a difference in the respondents' responses depending on the face-to-face survey. As a result of the analysis, it was confirmed that when a survey was conducted on PWDs, mixed results may appear according to the survey questions rather than the survey method. There was no difference in disability acceptance, which is a subjective content, according to the survey method, but there was a difference in house income, which is an objective matter, according to the survey method, resulting in conflicting results. When designing a survey for PWDs based on the results of this study, it is recommended to consider introducing non-face-to-face surveys for individual subjective or qualitative survey questions, but if objective or sensitive items such as income are included, more detailed consideration is needed when applying the survey method. 본 연구의 목적은 코로나19 등 변화하는 사회환경에 따라 도입되고 있는 비대면조사와 관련하여, 비대면조사 적용 여부에 따른 응답 내용의 통계적 차이를 검증한 후 장애인을 대상으로 적절한 조사방법을 모색하고자 하는 것이다. 이를 위해 2021년 장애인고용패널조사에 응답한 3,695명의 응답 결과를 기반으로 성향점수매칭과 회귀분석을 실시하였으며 대면조사 여부에 따라 응답자의 응답 내용에 차이가 있는지를 통계적으로 확인하였다. 분석 결과, 장애인 대상으로 설문조사를 할 때는 조사방법보다는 조사항목에 따라 혼재된 결과가 나타날 수 있음을 확인할 수 있었다. 주관적인 내용인 장애수용도는 조사방법에 따른 차이가 없었으나 객관적인 사항인 소득은 조사방법에 따른 차이가 있어 상반된 결과가 도출되었다. 본 연구결과를 토대로 장애인을 대상으로 설문조사를 설계할 경우, 개인의 주관적인 사항 또는 정성적인 설문조사 항목은 비대면조사를 도입하는 것을 검토해볼 수 있으나 소득과 같은 객관적인 사항 또는 민감항목이 포함되어 있다면 조사방법을 적용할 때 보다 세밀한 고려가 필요하며, 행정자료 연계와 같은 방안을 적극적으로 도입 및 활용할 것을 제언하였다.

A Comparative Study of Local Features in Face-based Video Retrieval

Zhou, Juan,Huang, Lan Korean Institute of Information Scientists and Eng 2017 Journal of Computing Science and Engineering Vol.11 No.1

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

SURF 특징점 추출 알고리즘을 이용한 얼굴인식 연구

강민구(Minku Kang),추원국(Wonkook Choo),문승빈(Seungbin Moon) 大韓電子工學會 2011 電子工學會論文誌-CI (Computer and Information) Vol.48 No.3

본 논문에서는 대표적인 특징점 추출 알고리즘인 SURF (Speeded Up Robust Features)를 이용한 얼굴 인식 방법을 소개한다. 일반적으로, SURF를 이용한 물체 인식은 특징점 추출 및 정합만을 수행하지만, 본 논문에서 제안하는 SURF를 이용한 얼굴 인식 방법은 특징점 추출 및 정합뿐만 아니라 얼굴 영상 회전 및 특징점 검증을 추가로 수행한다. 얼굴 영상 회전은 특징점의 수를 증가시키기 위해 수행되며, 특징점 검증은 정확하게 정합된 특징점들을 찾기 위해 수행된다. 비록 본 논문에서 제안한 SURF를 이용한 얼굴 인식 방법은 PCA를 이용한 방법보다 연산 시간이 더 요구되었지만, 인식률은 보다 더 높았다. 이러한 실험 결과를 통해, 특징점 추출 알고리즘도 얼굴 인식에 적용할 수 있음을 확인할 수 있었다. This paper proposes a SURF (Speeded Up Robust Features) based face recognition method which is one of typical interest point extraction algorithms. In general, SURF based object recognition is performed in interest point extraction and matching. In this paper, although, proposed method is employed not only in interest point extraction and matching, but also in face image rotation and interest point verification. image rotation is performed to increase the number of interest points and interest point verification is performed to find interest points which were matched correctly. Although proposed SURF based face recognition method requires more computation time than PCA based one, it shows better recognition rate than PCA algorithm. Through this experimental result, I confirmed that interest point extraction algorithm also can be adopted in face recognition.

A Comparative Study of Local Features in Face-based Video Retrieval

Juan Zhou,Lan Huang 한국정보과학회 2017 Journal of Computing Science and Engineering Vol.11 No.1

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

로봇 환경에서의 템플릿 매칭 기반 얼굴 인식 알고리즘의 비교 연구

한윤희(Yun-Hee Han),곽근창(Keun-Chang Kwak) 한국정보기술학회 2010 Proceedings of KIIT Conference Vol.2010 No.-

얼굴 인식을 수행하는 기술은 크게 기학학적 특징 정합 방법과 템플릿 매칭방법으로 분류 될 수 있다. 대부분의 얼굴 인식 시스템에서는 템플릿 매칭방법을 채택하고 있다. 본 논문에서는 vector기반 PCA, LDA, ICA와 matrix기반 2PCA, T-NPCA, T-NPCA-LDA에 대하여 살펴본다. 마지막으로, u-로봇 테스트베드 환경에서 얼굴 인식 데이터베이스를 구축하고, 알고리즘들의 성능을 비교한다. Face recognition technique can be largely categorized as Feature Matching and template matching. The most face recognition system adopt a template matching method. In this paper, explains vector-based PCA, LDA, ICA and matrix-based 2DPCA, T-MPCA, T-MPCA-LDA. Finally, we compares performance of face recognition algorithms based on face database constructed in u-robot test bed environments.