• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.2-41
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• 2002

The stereo correspondence of two retinal images is one of the most difficult problems in stereo vision because the reconstruction of 3-D scene is a typical visual ill-posed problem. So far there still have been many unsolved problems, one of which is to reconstruct 3-D scene for a monochromatic surface because there is no clue to make a correspondence between two retinal images. We consider this problem with two layered self-organization neural network to simulate the competitive and cooperative interaction of binocular neurons. A...

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.185-188
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• 2000

현재의 3차원 시각 정보 제시기는 Scene Graph 기반의 3차원 그래픽스 API에 기반을 두고 있다. 본 연구에서는 시각 정보 제시에 더불어 다양한 감각을 제시하기 위한 통합 제시 능력을 가지는 시스템으로 시각화 시스템을 확장하였다. 이 확장된 시스템은 다양한 감각 정보를 제시하기 위한 추가적인 정보를 가지는 확장된 Scene Graph을 가지고 운영되며, 통합된 Script System으로 각 감각 제시 시스템들간의 동기화 및 통합 관리와 제시 시스템의 확장에 유리한 장점을 가진다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.309-310
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• 2006

This paper presents an enhanced algorithm for compensating the visual quality in backlight image. Current cameras do not represent all details of scene into human's eye. Saturation and underexposure are common problems in backlight image. Retinex algorithm, derived from Land's theory on human visual perception is known to be effective in enhancing the contrast. However, its weaknesses are long processing time and low contrast of bright area in backlight scene because of compensating the details of dark area. In this paper, K-Retinex algorithm is proposed to reduce the processing time and enhance the contrast in both dark and bright area. To show the superiority of proposed algorithm, we compare the processing time and local variance of each area above.

• ETRI Journal
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• v.42 no.3
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• pp.399-410
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• 2020

Detecting visual relationships in an image is important in an image understanding task. It enables higher image understanding tasks, that is, predicting the next scene and understanding what occurs in an image. A visual relationship comprises of a subject, a predicate, and an object, and is related to visual, language, and spatial cues. The predicate explains the relationship between the subject and object and can be categorized into different categories such as prepositions and verbs. A large visual gap exists although the visual relationship is included in the same predicate. This study improves upon a previous study (that uses language cues using two losses) and a spatial cue (that only includes individual information) by adding relative information on the subject and object of the extant study. The architectural limitation is demonstrated and is overcome to detect all zero-shot visual relationships. A new problem is discovered, and an explanation of how it decreases performance is provided. The experiment is conducted on the VRD and VG datasets and a significant improvement over previous results is obtained.

• Korean Institute of Interior Design Journal
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• v.22 no.5
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• pp.293-301
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• 2013

The purpose of this study was to find the space perception by the scene and to analyze the characteristics in the exhibition space. The data for the analysis was collected through a questionnaire survey method. The questionnaire is composed of a scene selection on the panoramic photographs of the exhibition space. 'The 4 Rivers Cultural Center - The ARK' was selected as the subject of this survey. The results of the study are presented as follows : First, the space perception perceived imaged scenes rather than the specific elements of space. Second, the space perception was revealed through the 'Form', 'Materials', 'Light', 'Lighting', 'Furniture' and 'Media' of notable elements. Also that was perceived by forming 'Line', 'Surface' and 'Volume'. Particularly, the perception of 'Surface' was higher than 'Line' and 'Volume'. 'Surface' was perceived mostly through the 'Color'. The perception of 'Line' was positive to 'Boundary' or 'Continuous placement of the light'. In addition, the perception of 'Volume' was positive to 'The curve of the form', 'Transparent material', 'Three-dimensional elements'. Finally, The type of space perception was chosen as 'Extension', 'Center', 'Deep', 'Boundary' and 'Formative'. In this way, the results of this study will set a foundation for developing design methods to induce the space perception by the scene in the exhibition space.

• Journal of Digital Convergence
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• v.7 no.2
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• pp.93-102
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• 2009

Since video is composed of unstructured data with massive storage and linear forms, it is essential to conduct various research studies to provide the required contents for users who are accustomed to dealing with standardized data such as documents and images. Previous studies have shown the occurrence of undetected and false detected shots. This thesis suggested shot verification and video retrieval system using visual rhythm to reduce these kinds of errors. First, the system suggested in this paper is designed to detect the parts easily and quickly, which are assumed as shot boundaries, just by changing the visual rhythm without playing the image. Therefore, this enables to delete the false detected shot and to generate the unidentified shot and key frame. The following are the summaries of the research results of this study. Second, during the retrieving process, a thumbnail and keyword method of inquiry is possible and the user is able to put some more priorities on one part than the other between the color and shape. As a result, the corresponding shot or scene is displayed. However, in the case of not finding the preferred shot, the key picture frame of similar shot is supplied and can be used in the further inquiry of the next scene.

• ETRI Journal
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• v.33 no.4
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• pp.600-610
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• 2011

This paper presents a novel approach to face detection by localizing faces as the goal-specific saliencies in a scene, using the framework of selective visual attention of a human with a particular goal in mind. The proposed approach aims at achieving human-like robustness as well as efficiency in face detection under large scene variations. The key is to establish how the specific knowledge relevant to the goal interacts with the bottom-up process of external visual stimuli for saliency detection. We propose a direct incorporation of the goal-related knowledge into the specification and/or modification of the internal process of a general bottom-up saliency detection framework. More specifically, prior knowledge of the human face, such as its size, skin color, and shape, is directly set to the window size and color signature for computing the center of difference, as well as to modify the importance weight, as a means of transforming into a goal-specific saliency detection. The experimental evaluation shows that the proposed method reaches a detection rate of 93.4% with a false positive rate of 7.1%, indicating the robustness against a wide variation of scale and rotation.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.746-754
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• 2008

A 3D stereoscopic image is generated by interdigitating every scene with video editing tools that are rendered by two cameras' views in 3D modeling tools, like Autodesk MAX(R) and Autodesk MAYA(R). However, the depth of object from a static scene and the continuous stereo effect in the view of transformation, are not represented in a natural method. This is because after choosing the settings of arbitrary angle of convergence and the distance between the modeling and those two cameras, the user needs to render the view from both cameras. So, the user needs a process of controlling the camera's interval and rendering repetitively, which takes too much time. Therefore, in this paper, we will propose the 3D stereoscopic image editing system for solving such problems as well as exposing the system's inherent limitations. We can generate the view of two cameras and can confirm the stereo effect in real-time on 3D modeling tools. Then, we can intuitively determine immersion of 3D stereoscopic image in real-time, by using the 3D stereoscopic image preview function.

• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.5 s.118
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• pp.32-38
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• 2006

Roof greening in a city can contributes to not only providing network opportunities for dispersed greenspace patches but also bringing more greenspaces into a city. In addition, it can help to flooding and microclimate control in the city. Recently, a number of roof greening projects have been introduced, mainly to public buildings and schools. Roof peening need to offers both ecological functions and convenience and satisfaction for urban residents. This study aims to provide directions for improving ecological benefits and visual preference of roof greening. Twelve scene slides were adopted to measure people's visual preference. The survey results show that landscape images can be categorized into naturalness, visual diversity, uniqueness, and spatial flexibility. Physical scenes can be classified into type I mostly greened by plants, type II mixed between convenience facilities and plants, and type III constructed with pond. People show high preferences to type I and type II when visual diversity is high. The results of this study suggest to enhance the visual preference by considering visual diversity when applying the ecological design methods to improve naturalness for roof greening.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.12-21
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• 2023

Visual relationship understanding in computer vision allows to recognize meaningful relationships between objects in a scene. This technology enables the extraction of representative information within visual content. We discuss the technology of visual relationship understanding, specifically focusing on videos. We first introduce visual relationship understanding concepts in videos and then explore the latest existing techniques. Next, we present benchmark datasets commonly used in video visual relationship understanding. Finally, we discuss future research directions in video visual relationship understanding.