• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.317-318
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• 2019

가상/증강현실로 대표되는 공간정보 기반 실감형 콘텐츠에 대한 관심이 증대되면서 객체인식 등의 지능형 공간인지 기술에 대한 연구가 활발히 진행되고 있다. 특히 HMD등의 영상 시각화 장치의 발달 및 5G 통신기술의 출현으로 인해 실시간 대용량 영상정보의 송, 수신 및 가시화 처리 기술의 기반이 구축됨에 따라, $360^{\circ}$ 스트리밍 영상정보 처리와 같은 고자유도 콘텐츠를 위한 관련 연구의 필요성이 증대되고 있다. 하지만 지능형 영상정보 처리의 대표적 연구인 딥 러닝(Deep Learning) 기반 객체 인식 기술의 경우 대부분 일반적인 평면 영상(Planar Image)에 대한 처리를 다루고 있고, 파노라마 영상(Panorama Image) 특히, $360^{\circ}$ 스트리밍 영상 처리를 위한 연구는 미비한 상황이다. 본 논문에서는 딥 러닝을 이용하여 $360^{\circ}$ 스트리밍 영상에서의 객체인식 연구 방법에 대해 서술한다. 이를 위해 $360^{\circ}$ 카메라 영상에서 딥 러닝을 위한 학습 데이터를 획득하고, 실시간 객체 인식이 가능한 YOLO(You Only Look Once)기법을 이용하여 학습을 한다. 실험 결과에서는 학습 데이터를 이용하여 $360^{\circ}$영상에서 객체 인식 결과와, 학습 횟수에 따른 객체 인식에 대한 결과를 보여준다.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.284-291
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• 2005

I propose a framework for detecting, recognizing and classifying facial features based on learned expression patterns. The framework recognizes facial expressions by using PCA and expression HMM(EHMM) which is Hidden Markov Model (HMM) approach to represent the spatial information and the temporal dynamics of the time varying visual expression patterns. Because the low level spatial feature extraction is fused with the temporal analysis, a unified spatio-temporal approach of HMM to common detection, tracking and classification problems is effective. The proposed recognition framework is accomplished by applying posterior probability between current visual observations and previous visual evidences. Consequently, the framework shows accurate and robust results of recognition on as well simple expressions as basic 6 facial feature patterns. The method allows us to perform a set of important tasks such as facial-expression recognition, HCI and key-frame extraction.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.518-524
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• 2022

In this paper, we propose a method for combining convolutional neural networks and attention mechanism to improve the recognition performance of emotional stress from Electroencephalogram (EGG) signals. In the proposed method, EEG signals are decomposed into five frequency domains, and spatial information of EEG features is obtained by applying a convolutional neural network layer to each frequency domain. As a next step, salient frequency information is learned in each frequency band using a gate transformer-based attention mechanism, and complementary frequency information is further learned through inter-frequency mapping to reflect it in the final attention representation. Through an EEG stress recognition experiment involving a DEAP dataset and six subjects, we show that the proposed method is effective in improving EEG-based stress recognition performance compared to the existing methods.

• Korean Institute of Interior Design Journal
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• v.17 no.1
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• pp.146-154
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• 2008

The study aims to find out the changing aspects of contemporary Korean libraries so called public in terms of their spatial characteristics. In so doing, it analysed 16 recently built libraries by using the spatial depth defined in the Space Syntax theory. As the result, it could be said that the libraries were planned and designed well reflecting the world wide trend as a public institution such as an open plan, easy access, new functional spaces, and so on. It could be also said, however, that there was no difference between the previous libraries and the recent ones when the actual usage is considered. It means that the architectural attempts have been made to plan an 'open, public library', especially in terms of the spatial configuration, whereas the way of management has not been changed at all for some reasons such as the lack of staffs, security and so on. Therefore, it can be seen that the depth, one of the most important factors in the recognition of the spatial configuration, is more deepened as a form of the liner structure in the spatial configuration.

• Korean Institute of Interior Design Journal
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• v.15 no.6 s.59
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• pp.111-119
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• 2006

The spatial property of contemporary library is now rapidly changing through the spatial expansion of knowledge and information, the reduction of information storing facility, the variation of approaching methods by digital shift and the transition of social recognition as a cultural facility. Also the spatial characteristics with referring characters have developed such as, decentralization, de-construction, de-boundary, individual space, erasing of boundary, flow of space which extends infinitely. The main process of library origination, the systematic classification, and the storage system concluding with the demand and value of the information by changing social demands and the role of the widest ranged facility. And 5 themes, such as, hierarchy, center, storage, boundary, and symbol, as a changed spatial concept and analyzed in the case of library plans and libraries which are actually built. The significant purpose of this research is to propose that rhizomatous intellectuality and hypertext could be a theoretical background of the contemporary architecture and could be a viewpoint of the transition of spatial structure in libraries. A future library should have spatial property embracing various social changes and needs and for this respect, it is necessary to approach and analyze through the architectural explication from diverging points of view.

• Language and Information
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• v.18 no.2
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• pp.141-168
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• 2014

Recognizing spatial information associated with events expressed in natural language text is essential not only for the interpretation of such events and but also for the understanding of the relations among them. However, spatial information is rarely mentioned as compared to events and the association between event and spatial expressions is also highly implicit in a text. This would make it difficult to automate the extraction of spatial information associated with events from the text. In this paper, we give a linguistic analysis of how spatial expressions are associated with event expressions in a text. We first present issues in annotating narrative texts with reference relations between event and spatial expressions, and then discuss surface-level linguistic characteristics of such relations based on the annotated corpus to give a helpful insight into developing an automated recognition method.

• Korean Journal of Cognitive Science
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• v.23 no.2
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• pp.225-248
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• 2012

The summed-similarity model of visual short-term recognition proposes that the estimated amount of summed similarity between remembered items and a recognition probe determines recognition judgement decision (Kahan & Sekuler, 2002). This study examined the effect of a task-irrelevant location change on the recognition decision against two remembered Gabor gratings differing in their spatial frequencies. On each trial in Experiment, participants reported if two gratings displayed across the visual fields are the same or not as the probe grating displayed after about a second of memory delay. The probe grating would be the same as or different from the memory items (lure) by 1 or 4 JND units. The location of the probe would also vary randomly across the left and right visual field with respect to the location of the corresponding memory item. The participants were instructed to perform their recognition task exclusively to the spatial frequencies of the memory items and the probe while ignoring the potential location change of the probe. The results showed that false-recognition rates of the lure probe increased as the summed similarity between the memory items and the probe increased. The rates also further increased in the condition where the probe location was different from the location of the corresponding memory item compared to the condition where the probe location was the same. The increased false-recognition rates indicate that information stored into visual short-term memory is represented as a form of well-bound visual features rather than independent features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2632-2649
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• 2012

Most approaches to human action recognition is limited due to the use of simple action datasets under controlled environments or focus on excessively localized features without sufficiently exploring the spatio-temporal information. This paper proposed a framework for recognizing realistic human actions. Specifically, a new action representation is proposed based on computing a rich set of descriptors from keypoint trajectories. To obtain efficient and compact representations for actions, we develop a feature fusion method to combine spatial-temporal local motion descriptors by the movement of the camera which is detected by the distribution of spatio-temporal interest points in the clips. A new topic model called Markov Semantic Model is proposed for semantic feature selection which relies on the different kinds of dependencies between words produced by "syntactic " and "semantic" constraints. The informative features are selected collaboratively based on the different types of dependencies between words produced by short range and long range constraints. Building on the nonlinear SVMs, we validate this proposed hierarchical framework on several realistic action datasets.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.16-22
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• 2001

In this paper we mose a new scheme for recognition of deformed letters by extracting feature vectors based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are comprised of 2-D conditional moments which are invariant under translation, rotation, and scale of an image. The Algorithm for pattern recognition of deformed letters contains two parts: the extraction of feature vector and the recognition process. (i) We extract feature vector which consists of an improved 2-D conditional moments on the basis of estimated conditional Gibbs distribution for an image. (ii) In the recognition phase, the minimization of the discrimination cost function for a deformed letters determines the corresponding template pattern. In order to evaluate the performance of the proposed scheme, recognition experiments with a generated document was conducted. on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 96%.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.653-668
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• 2012

In this study, an improved HMM based recognition model is proposed for online English and Korean handwritten characters. The pattern elements of the handwriting model are sub character strokes and ligatures. To deal with the problem of handwriting style variations, a modified Hierarchical Clustering approach is introduced to partition different writing styles into several classes. For each of the English letters and each primitive grapheme in Korean characters, one HMM that models the temporal and spatial variability of the handwriting is constructed based on each class. Then the HMMs of Korean graphemes are concatenated to form the Korean character models. The recognition of handwritten characters is implemented by a modified level building algorithm, which incorporates the Korean character combination rules within the efficient network search procedure. Due to the limitation of the HMM based method, a post-processing procedure that takes the global and structural features into account is proposed. Experiments showed that the proposed recognition system achieved a high writer independent recognition rate on unconstrained samples of both English and Korean characters. The comparison with other schemes of HMM-based recognition was also performed to evaluate the system.