• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.556-558
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• 2022

This paper proposes a CanSat system with a vehicle tracking function based on Jetson Nano, a high-performance small computer capable of operating artificial intelligence algorithms. The CanSat system consists of a CanSat and a ground station. The CanSat falls in the atmosphere and transmits the data obtained through the installed sensors to the ground station using wireless communication. The existing CanSat is limited to the mission of simply transmitting the collected information to the ground station, and there is a limit to efficiently performing the mission due to the limited fall time and bandwidth limitation of wireless communication. The Jetson Nano based CanSat proposed in this paper uses a pre-trained neural network model to detect the location of a vehicle in each image taken from the air in real time, and then uses a 2-axis motor to move the camera to track the vehicle.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.147-156
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• 2024

This paper introduces the design of a turtle neck posture correction and prevention system for users of digital devices for a long time. The number of forward head posture patients in Korea increased by 13% from 2018 to 2021, and has not yet improved according to the latest statistics at the present time. Because of the nature of the disease, prevention is more important than treatment. Therefore, in this paper, we designed a system based on built-camera in most laptops to increase the accessiblility of the system, and utilize the features such as Pose Estimation, Face Landmarks Detection, Iris Tracking, and Depth Estimation of Google Mediapipe to prevent the need to produce artificial intelligence models and allow users to easily prevent forward head posture.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.103-108
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• 2024

In this paper, a smart elevator system was studied using real-time object detection technology based on YOLO(You only look once)v5. When an external elevator button is pressed, the YOLOv5 model analyzes the camera video to determine whether there are people waiting, and if it determines that there are no people waiting, the button is automatically canceled. The study introduces an effective method of implementing object detection and communication technology through YOLOv5 and MQTT (Message Queuing Telemetry Transport) used in the Internet of Things. And using this, we implemented a smart elevator system that determines in real time whether there are people waiting. The proposed system can play the role of CCTV (closed-circuit television) while reducing unnecessary power consumption. Therefore, the proposed smart elevator system is expected to contribute to safety and security issues.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.887-892
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• 2019

Many researchers have developed a series of vision-based technologies to monitor construction sites automatically. To achieve high performance of vision-based technologies, it is essential to build a large amount and high quality of training image database (DB). To do that, researchers usually visit construction sites, install cameras at the jobsites, and collect images for training DB. However, such human and site-dependent approach requires a huge amount of time and costs, and it would be difficult to represent a range of characteristics of different construction sites and resources. To address these problems, this paper proposes a framework that automatically constructs a training image DB using web crawling techniques. For the validation, the authors conducted two different experiments with the automatically generated DB: construction work type classification and equipment classification. The results showed that the method could successfully build the training image DB for the two classification problems, and the findings of this study can be used to reduce the time and efforts for developing a vision-based technology on construction sites.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.243-248
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• 2011

In this paper, we propose a new method to extract palm lines and read it with simple techniques from one photo. We use morphological information and 8-directional contour tracking algorithm. From the digitalized image, we transform original RGB information to YCbCr color model which is less sensitive to the brightness information. The palm region is extracted by simple threshold as Y:65~255, Cb:25~255, Cr:130~255 of skin color. Noise removal process is then followed with morphological information of the palm such that the palm area has more than quarter of the pixels and the rate of width vs height is more than 2:1 and 8-directional contour tracking algorithm. Then, the stretching algorithm and Sobel mask are applied to extract edges. Another morphological information that the meaningful edges(palm lines) have between 10 and 20 pixels is used to exclude noise edges and boundary lines of the hand from block binarized image. Main palm lines are extracted then by labeling method. This algorithm is quite effective even reading the palm from a photographed by a mobile phone, which suggests that this method could be used in various applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.568-576
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• 2003

This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.1-8
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• 2001

In this paper, we propose an algorithm which estimates the displacements and velocities of objects in the soccer field from the soccer image sequences. Assuming the time interval of an object movement is given, we transform the object positions into those in the soccer field model and compute the distance and the velocity. When four corresponding pairs of the feature points, such as the crossing points of the lines in the soccer field, exist and three of them are not on a line, we transform the object positions in the soccer image into those in the soccer field by using the perspective displacement field model. In addition, when the soccer image has less than four feature points, we first transform the object positions into those in the image which has more than four feature points, and then transform the positions into those in the soccer field again. To find the coordinate transformation between two images, we estimate the panning and zooming for consecutive images in the sequence. In the experimental results, we quantitatively evaluated the estimation accuracy by applying our algorithm to the synthetic. soccer image sequences generated by graphic tools, and applied it to the real soccer image sequences for broadcasting to show its usefulness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1597-1609
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• 2004

A lot of lipreading system has been proposed to compensate the rate of speech recognition dropped in a noisy environment. Previous lipreading systems work on some specific conditions such as artificial lighting and predefined background color. In this paper, we propose a real-time lipreading system which allows the motion of a speaker and relaxes the restriction on the condition for color and lighting. The proposed system extracts face and lip region from input video sequence captured with a common PC camera and essential visual information in real-time. It recognizes utterance words by using the visual information in real-time. It uses the hue histogram model to extract face and lip region. It uses mean shift algorithm to track the face of a moving speaker. It uses PCA(Principal Component Analysis) to extract the visual information for learning and testing. Also, it uses HMM(Hidden Markov Model) as a recognition algorithm. The experimental results show that our system could get the recognition rate of 90% in case of speaker dependent lipreading and increase the rate of speech recognition up to 40～85% according to the noise level when it is combined with audio speech recognition.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1031-1041
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• 1999

기존의 한글에 대한 입술 애니메이션 방법은 음소의 입모양을 몇 개의 입모양으로 정의하고 이들을 보간하여 입술을 애니메이션하였다. 하지만 발음하는 동안의 실제 입술 움직임은 선형함수나 단순한 비선형함수가 아니기 때문에 보간방법에 의해 중간 움직임을 생성하는 방법으로는 음소의 입술 움직임을 효과적으로 생성할 수 없다. 또 이 방법은 동시조음도 고려하지 않아 음소들간에 변화하는 입술 움직임도 표현할 수 없었다. 본 논문에서는 동시조음을 고려하여 한글을 자연스럽게 발음하는 입술 애니메이션 방법을 제안한다. 비디오 카메라로 발음하는 동안의 음소의 움직임들을 측정하고 입술 움직임 제어 파라미터들을 추출한다. 각각의 제어 파라미터들은 L fqvist의 스피치 생성 제스처 이론(speech production gesture theory)을 이용하여 실제 음소의 입술 움직임에 근사한 움직임인 지배함수(dominance function)들로 정의되고 입술 움직임을 애니메이션할 때 사용된다. 또, 각 지배함수들은 혼합함수(blending function)와 반음절에 의한 한글 합성 규칙을 사용하여 결합하고 동시조음이 적용된 한글을 발음하게 된다. 따라서 스피치 생성 제스처 이론을 이용하여 입술 움직임 모델을 구현한 방법은 기존의 보간에 의해 중간 움직임을 생성한 방법보다 실제 움직임에 근사한 움직임을 생성하고 동시조음도 고려한 움직임을 보여준다.Abstract The existing lip animation method of Hangul classifies the shape of lips with a few shapes and implements the lip animation with interpolating them. However it doesn't represent natural lip animation because the function of the real motion of lips, during articulation, isn't linear or simple non-linear function. It doesn't also represent the motion of lips varying among phonemes because it doesn't consider coarticulation. In this paper we present a new coarticulation model for the natural lip animation of Hangul. Using two video cameras, we film the speaker's lips and extract the lip control parameters. Each lip control parameter is defined as dominance function by using L fqvist's speech production gesture theory. This dominance function approximates to the real lip animation of a phoneme during articulation of one and is used when lip animation is implemented. Each dominance function combines into blending function by using Hangul composition rule based on demi-syllable. Then the lip animation of our coarticulation model represents natural motion of lips. Therefore our coarticulation model approximates to real lip motion rather than the existing model and represents the natural lip motion considered coarticulation.