• Educational Technology International
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• v.8 no.1
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• pp.1-16
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• 2007

The general aim of this article is to explicate what can be researched in our field based on the new understanding on the ability of human visual intelligence. To follow this aim, three key discussions were followed. The first is to explain why the human visual intelligence research is so important in our field and how it was neglected. The basic orientations of the research questions used in its framing and in answering are reviewed. After reviewing traditional research orientations, as the second discussion, alternative, more useful perspective for thinking about human visual intelligence is suggested. And the possibility of contribution for the future research in general is discussed. In doing so, human visual intelligence was defined in rather practically oriented ways rather than theoretically oriented ones. More practical perspectives were suggested. The third discussion is to show how to use the alternative perspectives of human visual intelligence in the areas of educational technology research. It was hoped that the article lays out conceptual groundwork for generation of educational technology research frameworks which can be used for the research conduct, reproduction and sharing by adopting practically oriented views on human visual intelligence as a new territory of educational technology research.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.451-454
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• 2003

A new query method, called query by visual keys, is proposed to aim easy operation and efficient region-based image retrieval (RBIR). Visual keys are constructed from representative regions/subimages in a given image database, and the database is indexed with visual keys. A system on PC is presented, where text retrieval techniques are applied to the image retrieval with visual keys. Experimental results show that one retrieval is done within 4ms and that the proposed system achieves the comparable retrieval precision (with user-friendly operation and low computational cost) to conventional region based image retrieval systems

• Journal of Korean Elementary Science Education
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• v.39 no.3
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• pp.369-381
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• 2020

This study aims to analyse the relationship between multiple intelligence and scientific creativity of science-gifted elementary students focusing on the subject of biology. For this, 37 science-gifted fifth-graders in the Science-Gifted Education Center at an Office of Education conducted a multiple intelligence test. In addition, researchers collected science-gifted students' results of scientific creativity activity at the botanical garden field trip. The main findings from this study are as follows: First, strong intelligence was logical-mathematical intelligence for gifted students, and weak intelligence was found to be naturalistic intelligence for them. Second, there was no significant correlation in the relationship between multiple intelligence and scientific creativity of science-gifted students. Third, as a result of independent two sample t-test for each intelligence and scientific creativity scores divided into the upper and lower groups, only verbal-linguistic intelligence statistically differed significantly at the level of p<.05 (t=2.13, df=35, p=0.04). Fourth, as a result of conducting a two-way analysis to see if there were any interaction effects, verbal-linguistic and visual-spatial, logical-mathematical and visual-spatial, logical-mathematical and bodily-kinesthetic, and visual-spatial and musical-rhythmic intelligence all showed significant values at the level of p<.05 level in interaction effects on originality element comprising scientific creativity. Fifth, an analysis of students with high naturalistic intelligence showed that their scores of scientific creativity tasks conducted at the botanical garden field trip were all lower. Based on the results of this study, this study discussed the implications of scientific creativity learning linking multiple intelligence in primary science education and gifted education.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.113-118
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• 1997

This paper proposes a object tracking method based on the local moments, or moment based on the local moments, or moment of some restricted area, in which the idea of the viewpoint and the visual filed corresponding to the local area of an image is introduced. Using local moment with the optimally controlled viewpoint and visual field, the target position and its breadth are estimated robustly. By two experiments, the validity of the proposed method is shown.

• ETRI Journal
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• v.45 no.5
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• pp.795-810
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• 2023

Unmanned aerial vehicles (UAV) and ground vehicles (UGV) require advanced video analytics for various tasks, such as moving object detection and segmentation; this has led to increasing demands for these methods. We propose a zero-shot video object segmentation method specifically designed for UAV and UGV applications that focuses on the discovery of moving objects in challenging scenarios. This method employs a background memory model that enables training from sparse annotations along the time axis, utilizing temporal modeling of the background to detect moving objects effectively. The proposed method addresses the limitations of the existing state-of-the-art methods for detecting salient objects within images, regardless of their movements. In particular, our method achieved mean J and F values of 82.7 and 81.2 on the DAVIS'16, respectively. We also conducted extensive ablation studies that highlighted the contributions of various input compositions and combinations of datasets used for training. In future developments, we will integrate the proposed method with additional systems, such as tracking and obstacle avoidance functionalities.

• Journal of Korea Entertainment Industry Association
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• v.15 no.1
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• pp.53-62
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• 2021

After the first to present projected moving pictures to audiences, the film industry has been reshaping along with technological advancements. Through the full-scale introduction of visual effects-oriented post-production and digital technologies in the film-making process, the film industry has not only undergone significant changes in the production, but is also embracing the cutting edge technologies broadly and expanding the scope of industry. Not long after the change to digital cinema, the concept of artificial intelligence, first known at the Dartmouth summer research project in 1956, before the digitalization of film, is expected to bring about a big transformation in the film industry once again. Large volume of clear digital data from digital film-making makes easy to apply recent artificial intelligence technologies represented by machine learning and deep learning. The use of artificial intelligence techniques is prominent around major visual effects studios due to automate many laborious, time-consuming tasks currently performed by artists. This study aims to predict how artificial intelligence technology will change the film industry in the future through analysis of visual effects production cases using artificial intelligence technology as a production tool and to discuss the industrial potential of artificial intelligence as visual effects technology.

• The Journal of Sustainable Design and Educational Environment Research
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• v.13 no.1
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• pp.69-74
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• 2014

Intelligence of children is developed by psychological factors, and these are affected much by visual cognition. Language, behavior, arts, and cultural environment would be the main factors for visual cognitions of children. Therefore, the aim of this study is to set up those data for children intelligence development. For this, I researched, analyzed, and evaluated the esthetic consciousness of children on visual arts.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.15-28
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• 2019

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.205-208
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• 2024

Artificial Intelligence (AI) technology has evolved rapidly in recent years and is used in everything from banking to email management to surgery, but without the help of the visible, most of the fun features of the Internet include visual impairment. It benefits people with disabilities. The main purpose of this study is to find ways to help people with visual impairments using AI technology. A visually impaired request is made for the visually impaired. For example, when a message arrives that the program will notify you by voice (reads the sender's name, read the message, and replies to it if necessary), this is a special program installed on your mobile phone. This program uses a customized algorithm developed in Python to convert written text to voice, read text, and convert voice to written text on a message when a visually impaired person wants to respond. Then it sends the response in the form of a text message. Therefore, the research should lead to programs for people with visual impairments. This program makes mobile phones easier and more comfortable to use and makes the daily life easier for visual impairments.