• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.409-414
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• 2023

In recent years, the emergence of a number of AI image generation software represented by [Midjourney] has brought great impetus to the development of the field of AI-assisted art creation. Compared with the traditional hand-painted digital painting with the aid of electronic equipment, broke the traditional sense of animation character creation logic.This paper analyzes the application of AI technology in the field of animation character design through the practice of two-dimensional animation character . This is having a significant impact on the productivity and innovation of animation design and character modeling. The key results of the analysis indicate that AI technology, particularly through the utilization of "Midjourney,"enables the automation of certain design tasks, provides innovative approaches, and generates visually appealing and realistic characters. In conclusion, the integration of AI technology, specifically the application of "Midjourney," brings a new dimension to animation character design. The utilization of AI image generation software facilitates streamlined workflows, sparks creativity, and improves the overall quality of animated characters. As the animation industry continues to evolve, AI-assisted tools like "Midjourney" hold great potential for further advancement and innovation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1A
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• pp.25-32
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• 2010

Recently a passenger ship and liner has been spread throughout men of diversity, the space and informations is not open to general passenger. Therefore security systems are necessary for special sailors to admit them. Although security systems has a variety usage methods which are organism recognition(finger printer, iritis and vein etc) a few years ago, these usages has a defect reusing other objects because of leaving a trace. Therefore this paper designs and implements using 3D Qube image password interface which hand gestures are recognized after acquiring from 2D input image for protective marker of finger printer.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1732-1739
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• 2018

With the explosion of digital devices, interaction technologies between human and devices are required more than ever. Especially, hand gesture recognition is advantageous in that it can be easily used. It is divided into the two groups: the contact sensor and the non-contact sensor. Compared with non-contact gesture recognition, the advantage of contact gesture recognition is that it is able to classify gestures that disappear from the sensor's sight. Also, since there is direct contacted with the user, relatively accurate information can be acquired. Electromyography (EMG) and force-sensitive resistors (FSRs) are the typical methods used for contact gesture recognition based on muscle activities. The sensors, however, are generally too sensitive to environmental disturbances such as electrical noises, electromagnetic signals and so on. In this paper, we propose a novel contact gesture recognition method based on Flexible Epidermal Tactile Sensor Array (FETSA) that is used to measure electrical signals according to movements of the wrist. To recognize gestures using FETSA, we extracted feature sets, and the gestures were subsequently classified using the support vector machine. The performance of the proposed gesture recognition method is very promising in comparison with two previous non-contact and contact gesture recognition studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1977-1985
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• 2007

The character recognition technique is one of the artificial intelligence and has been widely applied in the automated system robot HCI(Human Computer Interaction), etc. This paper introduces the character set and the representative character that can be used in the recognition of the mage ROI. The character codes in this ROI include the digit, symbol, English and Hereat etc. We proposed the efficient multi-classifier structure by combining the small-size classifiers hierarchically. Moreover, we generated each small-size classifiers by delta-bar-delta learning algorithm. We tested the performance with various kinds of images and achieved the accuracy of 99%. The proposed multi-classifier showed the efficiency and the reliability for the mixed character code set.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2505-2528
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• 2023

The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.72-89
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• 2024

Depression is a common disorder among the elderly, significantly affecting their quality of life. Traditional dance interventions, although beneficial, have limitations in convenience, personalization, and retention. With the advent of digital technology, digital dance interventions have emerged as a potential solution to these limitations. This paper involves an extensive review of literature on digital dance interventions. Research databases were searched for studies that focus on the use of digital dance in treating depression among older adults. The review also includes analyses of the advancements in digital dance technology, its application in therapeutic settings, and the evaluation of its efficacy. The paper identifies three main challenges in the current digital dance intervention research: real-time dynamic assessment, multimodal dance generation, and improving compliance. Despite these challenges, digital dance interventions show promise in addressing the limitations of traditional dance therapy. The research suggests that the integration of human-computer interaction and personalized approaches in digital dance interventions could significantly improve outcomes in elderly patients with depression. Digital dance interventions represent a novel and promising approach to treating depression in older adults. Future research should focus on overcoming the identified challenges and enhancing the effectiveness of these interventions.

• Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.153-160
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• 2014

As smartphones came into wide use recently, it has become increasingly popular not only among young people, but among middle-aged people as well. Most smartphones adopt capacitive full touch screen, so touch commands are made by fingers unlike the PDAs in the past that use touch pens. In this case, a significant portion of the smartphone's screen is blocked by the finger so it is impossible to see the screens around the finger touching the screen; this causes difficulties in making precise inputs. To solve this problem, this research proposes a method of using simple AR markers to improve the interface of smartphones. A marker is placed in front of the smartphone camera. Then, the camera image of the marker is analyzed to determine the position of the marker as the position of the mouse cursor. This method can enable click, double-click, drag-and-drop used in PCs as well as touch, slide, long-touch-input in smartphones. Through this research, smartphone inputs can be made more precise and simple, and show the possibility of the application of a new concept of smartphone interface.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.2
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• pp.150-161
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• 2012

Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ms in a VGA image.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.295-300
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• 2009

This paper presents a context-aware information service system in public places that have complex processes, for the disabled and the elderly. The system infers context of a user which is derived from the user's demand, then it informs to the user -what to do, where to go-according to the context. Our system gets user's context from sensor data and informations from the local information system. The system provides more suitable information with a knowledge model, which organizes location and process data coordinately. The information is provided personally to the user, with mobile devices.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.53-62
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• 2004

The processing of emotional information is very important in Human-Computer Interaction (HCI). In particular, it is very important in video information processing to deal with a user's affection. To handle emotional information, it is necessary to represent meaningful features and detect them efficiently. Even though it is not an easy task to detect emotional events from low level features such as colour and motion, it is possible to detect them if we use statistical analysis like Linear Discriminant Analysis (LDA). In this paper, we propose a representation scheme for emotion-related features and a defection method. We experiment with extracted features from video to detect emotional events and obtain desirable results.