• 한국실내디자인학회논문집
• /
• 제14권2호
• /
• pp.188-196
• /
• 2005

The light has been considered as a main character that can not be omitted in architecture since ancient time. The recognition of space by light means that light makes the fictional space recognizable concretization. Light and shade make emptiness and substance can be easily recognized. Also reiteration and location of light and shade change the degree of acknowledgement. The character of light can strengthen or weaken the power of recognition concerning territory, direction and location. Also it can broaden, close, and segregate the domain and eventually strengthen recognition. In this study, I will try to find how space can be recognized with the help of light in architectural territories in terms of actual states. Also the main aim of my study will be the study of the light application in real space with the architectural example of space recognition by light and possible opportunity of it in space plan.

• 제어로봇시스템학회논문지
• /
• 제5권7호
• /
• pp.821-826
• /
• 1999

This paper proposes a face recognition method using feature spaces and image vectors in the image plane. We obtain the 2-D feature space using the self-organizing map which has two inputs from the axis of the given image. The image vector consists of its weights and the average gray levels in the feature space. Also, we can reconstruct an normalized face by using the image vector having no connection with the size of the given face image. In the proposed method, each face is recognized with the best match of the feature spaces and the maximum match of the normally retrieval face images, respectively. For enhancing recognition rates, our method combines the two recognition methods by the feature spaces and the retrieval images. Simulations are conducted on the ORL(Olivetti Research laboratory) images of 40 persons, in which each person has 10 facial images, and the result shows 100% recognition and 14.5% rejection rates for the 20$\times$20 feature sizes and the 24$\times$28 retrieval image size.

• 한국실내디자인학회논문집
• /
• 제17권4호
• /
• pp.92-101
• /
• 2008

A new paradigm of design lays stress on the world of metaphysical concepts, and various attempts are being made to give meaning to psychological values. Hotel is a memorable place to remind of a special moment in one's life such as travel, marriage, meeting and so on. It also contains even more symbolism than other spaces as it is the place where the most primary and private act takes place apart from one's residence. As a result, it is also possible to communicate the message which a designer intends to convey through the user's recognition in the form of various symbolic expressions in space design. The designer communicates a meaning into a space through a symbolic system and creates a mutual consensus by means of the understanding structure of "designer-space-user". The user's diverse interpretations through a symbol are based on epistemology and consist of the primary, the secondary and the tertiary recognition structure system in the aspect of their contents. The primary structure depends on sensual perception, impressive idea and transcendental recognition based on metaphysical and perceptional association. The secondary structure includes casualty, continuous deduction and rational(integral) recognition. Finally, the tertiary structure is sublimation to the transcendental mental world beyond the boundary of emotion and it is classified into fundamental recognition structure on an object and archetypical recognition structure on an ego. These characteristics can derive systematic understandings and diverse interpretations on the symbol from the space of a hotel through the frame of analysis based on the artistic form of monosemous, polysemous and multidimensional frameworks and symbols. The framework of this analysis includes all the cases, and various methods which haven't been attempted in practice are presented. Therefore this study is not just a simple analysis of space but rather it will serve as a methodological tool for design that allows for various attempts of symbolic design concepts in the recognition structure system.

• 대한지리학회지
• /
• 제46권6호
• /
• pp.767-780
• /
• 2011

이 논문은 '인정(recognition)'을 통해 인간과 공간의 관계에 대해 살펴보았다. 인정은 인간의 근원적 욕구이다. 인간은 누구든지 어디서나 인정받으려 한다. 자신의 정체성을 강화하고, 자신의 존재이유를 확인받기 위해 인정투쟁을 벌인다. 헤겔이 제시한 '인정'은 주체-객체의 인간관에 근거한 상호인정 과정에 근거한다. 반면에, 서로 주체성을 토대로 하는'인정'은 나와 너의 관계를 토대로'우리'를 강조하는 인간관에 근거한다. '인정'은 인간과 공간의 관계에 대한 새로운 인식을 가능하게 한다. 지금까지 지리학에서 다루었던 보이는 공간에 대한 지리적 인식을 넘어, 보이지 않는 공간에 대한 지리학의 역할을 채근한다. 보이지 않는 공간을 보이게 하는 과정을 통해 지리학의 본질을 회복하는데 기여한다. 목소리가 들리지 않는 공간과 이야기가 쓰여지지 않는 공간에 담겨있는 지리적 의미를 발견하도록 돕는다. 이를 통해 우리 사회의 모순과 부조리한 모습을 고발하고, 본질적으로 문제를 해결할 수 있는 방법을 제시한다. 이같은 논의의 궁극적 목적은 지리학이 당면한 위기를 극복하고, 인문학으로서 세상과 소통하기 위한 것이다.

• 한국멀티미디어학회논문지
• /
• 제21권5호
• /
• pp.626-637
• /
• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

• 제어로봇시스템학회논문지
• /
• 제4권6호
• /
• pp.765-771
• /
• 1998

An artificial neural network(NN) technique is developed for hardware redundant sensor validation. Since the measurement space is a continuous space with many operating regions, it is difficult to train a NN to correctly detect failure in an accurate measurement system. A conventional backpropagation NN is modified to include an additional preprocessing layer that extracts classification features from scalar measurements. This feature extraction means transform the measurement space to parity space. The NN is independent of the state variable being measured, the instrument range, and the signal tolerance. This NN resembles the parity space approach to signal validation, except that analytical parity equations are unneeded and the NN pattern recognition capability is utilized for decision making.

• ETRI Journal
• /
• 제37권6호
• /
• pp.1220-1230
• /
• 2015

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

• ETRI Journal
• /
• 제40권4호
• /
• pp.499-510
• /
• 2018

A vector space based augmented structural kinematic (VSASK) feature descriptor is proposed for human activity recognition. An action descriptor is built by integrating the structural and kinematic properties of the actor using vector space based augmented matrix representation. Using the local or global information separately may not provide sufficient action characteristics. The proposed action descriptor combines both the local (pose) and global (position and velocity) features using augmented matrix schema and thereby increases the robustness of the descriptor. A multiclass support vector machine (SVM) is used to learn each action descriptor for the corresponding activity classification and understanding. The performance of the proposed descriptor is experimentally analyzed using the Weizmann and KTH datasets. The average recognition rate for the Weizmann and KTH datasets is 100% and 99.89%, respectively. The computational time for the proposed descriptor learning is 0.003 seconds, which is an improvement of approximately 1.4% over the existing methods.

• 한국실내디자인학회논문집
• /
• 제23권5호
• /
• pp.41-50
• /
• 2014

In relation to spatial expression, the remediation theory of Jay David Bolter & Richard Grusin shows a sufficient possibility of providing extended idea and experience through the space of critical representation. The remediation theory discussed in the scope of new media says about the existence method and the development process of media through immersion into media and awakening, and one attribute of remediation which aims at the extension of another realistic experience and recognition through various media, contains common denominators which display diversity and complexity of installation space, and use the audience as expression elements. Therefore, this study aims to apply the remediation theory in order to interpret space using more diverse and multisensory expression methods. For achieving this purpose, this study found the connection among characteristics of hypermediacy which is an axis of installation and remediation theory, and analyzed diverse cases regarding installation space and characteristics of hypermediacy, depending on external aspects of form and expression and internal aspects of experience and cognition. The method of hypermediation expression in installation space converts the recognition about the basic custom of new experience, space and representation. This means that the logic of remediation could approach space by leading to more extended form and recognition. In conclusion, the characteristics of space and the possibility of extended expression revealed in the relationship between installation space and hypermediacy logic would provide another developmental significance for research on space design.

• 조명전기설비학회논문지
• /
• 제12권3호
• /
• pp.74-82
• /
• 1998

본 연구에서는 초음파 센서에 의해 물체정보를 획득하고 불변모멘트 백터를 이용하여 이동 및 회전에 불변하는 물체특정점올 추출한다. 그리고 이를 SQFM(냉f요R없비1핑 Feature Map) 신경회로망의 입력데이터로 사용하여 물체의 이동 및 회전에 무관한 물체인식 시스템을 제안하였다. 또한 SOFM 신경회로망의 출력 neuron space 크기 및 반복학습회수와 물체인식률과의 관계를 실험하였다. 출력 neuron space와 반복학습회수를 각각 $4\times4~10\times10$까지, 10~50회까지 변화시쳐 물체인식올 실험한 결과 물체인식률은 동일한 값인 92.3[% 를 나타내었다.