• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.97-108
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• 2022

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.783-786
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• 2021

In recent years, the use of LiDAR sensors is increasing as autonomous driving, robot control, and drones are considered more. Contrary to ordinary cameras, LiDAR sensors make it possible to handle challenging problems by calculating the distance between objects. This crucial characteristic makes more active research on deep learning models dealing with point clouds which are data of LiDAR. In this paper, among the schemes of using the point cloud, the Point-based approach is mainly discussed. Furthermore, future streams and insights can be considered by looking at solving methods and the limitations.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.93-103
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• 2023

The problem of reconstructing three-dimensional models of people and objects from color and depth images captured by low-cost RGB-D cameras has long been an active research area in computer graphics. Color and depth images captured by low-cost RGB-D cameras are represented as point clouds in three-dimensional space, which correspond to discrete values in a continuous three-dimensional space and require additional surface reconstruction compared to rendering using polygonal models. In this paper, we propose an effective ray-tracing based technique for visualizing point clouds rather than polygonal models. In particular, our method shows the possibility of an effective rendering method even in mobile environment which has limited performance due to processor heat and lack of battery.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1485-1490
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user, does face recognition and vital for many surveillance based systems. Advantage of face recognition when compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to decrease in dimension from of image acquisition step and various changes associated with face pose and background. Factors that deteriorate performance of face recognition are many such as distance from camera to face, lighting change, pose change, and change of facial expression. In this paper, we implement a new 3D active camera system to prevent various pose variation that influence face recognition performance and propose face recognition algorithm for intelligent surveillance system and mobile robot system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.27-34
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• 2011

In this paper, we propose an active 3D shape acquisition method based on photometric stereo using camera and flash on a smartphone. Two smartphones are used as the master and slave, in which the slave projects illumination from different locations while the master captures the images and processes photometric stereo algorithm to reconstruct 3D shape. In order to reduce the error, the smartphone's camera is calibrated to overcome the effect of the lens distortion and nonlinear camera sensor response. We apply 5-point algorithm to estimate the pose between smartphone cameras and then estimate lighting direction vector to run the photometric stereo algorithm. Experimental result shows that the proposed system enables us to use smartphone as a 3D camera with low cost and high quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.155-164
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user and is able to doface recognition, which is vital for many surveillance-based systems. The advantage of face recognition compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to the decreasing in dimension from image acquisition step and various changes associated with face pose and background. There are many factors that deteriorate performance of face recognition such as thedistance from camera to the face, changes in lighting, pose change, and change of facial expression. In this paper, we implement a new sliding active camera system to prevent various pose variation that influence face recognition performance andacquired frontal face images using PCA and HMM method to improve the face recognition. This proposed face recognition algorithm can be used for intelligent surveillance system and mobile robot system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.139-146
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• 2014

This paper proposes an efficient method for automatically distinguishing various facial expressions. To recognize the emotions from facial expressions, the facial images are obtained by digital cameras, and a number of feature points were extracted. The extracted feature points are then transformed to 49-dimensional feature vectors which are robust to scale and translational variations, and the facial emotions are recognized by statistical pattern classifiers such Naive Bayes, MLP (multi-layer perceptron), and SVM (support vector machine). Based on the experimental results with 5-fold cross validation, SVM was the best among the classifiers, whose performance was obtained by 50.8% for 6 emotion classification, and 78.0% for 3 emotions.

• The Research Journal of the Costume Culture
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• v.18 no.5
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• pp.991-1002
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• 2010

Nowadays, personal media is a new tool for communication as digital cameras and mobile phones are developing rapidly. We are concerned over Cyworld users who could have different personal characteristics which will influence on buying patterns in on line shopping behaviors. The purpose of this research was to observe fashion attitudes and purchase behavior of Cyworld mini homepage users, for establishing marketing strategies by understanding consumers. For this study, one line survey was used for 500 male and female subjects who are 20 to 40 years old. Only reliable 441 questionnaires were used for analysis. The SPSS program was used for frequency, K-means cluster, t test, and chi-square test. A total of 441 respondents were clustered on the basis of 8 item self-disclosure scale, using the K-means procedures. The results indicated that respondents were clustered into two segments; 267 respondents(active attitude towards self-disclosure) and 164 ones(not active). We examined fashion attitudes in mini home page and buying behavior by self-disclosed variable. Those who are involved actively in self expression and self-disclosure considered more fashion style and trend. The major motivates of web surfing was finding a good design, and good price. High self-disclosure group tends to search many shopping mall for right design and low self disclosure group tends to search them for the right price. High self-disclosure group tend to shop the fashion products more, while low self disclosure group tend to purchase books more through the internet. We realized that active group in self-disclosure purchased their clothing accidently when they visit Cyworld.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.311-316
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• 2018

An antenna-coupled bolometer-type terahertz sensor was designed, fabricated, evaluated, and utilized to obtain terahertz transmission images. The sensor consists of a thin film bowtie antenna that resonates accordingly in response to an incident terahertz beam, a heater that converts the applied current in the antenna into heat, and a microbolometer that converts the rise in temperature into a change in resistance. The device is fabricated by a bulk micromachining process on a 4-inch silicon wafer. The fabricated sensor chip has a size of $2{\times}2mm$ and an active area of $0.1{\times}0.1mm^2$. The temperature coefficient of resistance (TCR) of the bolometer film (VOx) is 2.0%, which is acceptable for bolometer applications. The output sensor signal is proportional to the power of the incident terahertz beam. Transmission images were obtained with a 2-axis scanning imaging system that contained the sensor. The small active area of the sensor will enable the development of highly sensitive focal plane array sensors in terahertz imaging cameras in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.119-126
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• 2012

Recently, we used to recognize for human motions with some recognition algorithms. examples, HMM, DTW, PCA etc. In many human motions, we concentrated our research on recognizing fighting motions. In previous work, to obtain the fighting motion data, we used motion capture system which is developed with some active markers and infrared rays cameras and 3 dimension information converting algorithms by the stereo matching method. In this paper, we describe that the different method to acquiring 3 dimension fighting motion data and a HMM algorithm to recognize the data. One of the obtaining 3d data we used is depth map algorithm which is calculated by a stereo method. We test the 3d acquiring and the motion recognition system, and show the results of accuracy and performance results.