• Journal of Information Technology Applications and Management
• /
• v.28 no.6
• /
• pp.145-161
• /
• 2021

Recently, as personal information utilization devices such as IoT, artificial intelligence, and wearable devices that focus on the individual have spread, privacy violations are also increasing. However, the privacy paradox of providing personal information to enjoy services while worrying is getting stronger. However, there are still preliminary studies on this. In this study, an intelligent home camera based on IoT technology was selected as a research object, and whether privacy paradox exists in the IoT environment, including smart home camera, was studied. To this end, the effect of perceived usefulness, a benefit factor of smart home camera use, and privacy concern, a risk factor, on intention to use was verified. In addition, it was investigated whether the relationship between privacy concerns and intention to use differs according to the presence or absence of use experience. In order to verify the research model, a survey was conducted with people with and without experience in using smart home cameras, and a total of 298 data samples were used for statistical analysis. As a result of the analysis, it was found that both perceived usefulness and privacy concerns had a positive effect on the intention to use, proving that privacy paradox exists in the IoT-based smart home camera environment. In addition, by analyzing the fact that privacy concerns have different effects on usage intentions depending on the user experience, it was verified that those with experience have a strong privacy paradox and those without experience have a weak privacy paradox. This study is meaningful because it seeks strategic implications to improve service and business performance by understanding the relationship between privacy attitudes and behaviors of IoT service providers, including smart home cameras.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.2
• /
• pp.39-44
• /
• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.6
• /
• pp.537-546
• /
• 2019

The paper actualizes the twin camera module system that is portable and very useful for the production of 3D contents. The suggested twin camera module system is a system to be able to display the 3D image after converting the inputted image from 2D stereo camera. To evaluate the performance of the twin camera module suggested in this paper, I assessed the correction of Rotation and Tilt created depending on the visual difference between the left and right stereoscopic image shot by the left and right lenses by using the Test Platform. In addition, I verified the efficiency of the twin camera module system through verifying Depth Error of 3D stereoscopic image by means of Scale Invariant Feature Transform(SIFT) algorithm. I think that if the user utilizes the suggested twin camera module system in displaying the image to the external after converting the shot image into the 3D stereoscopic image and the preparation image, it is possible to display the image in a matched way with an output device fit respectively for different 3D image production methods and if the user utilizes the system in displaying the created image in the form of the 3D stereoscopic image and the preparation image via different channels, it is possible to produce 3D image contents easily and conveniently with applying to lots of products.

• Journal of Broadcast Engineering
• /
• v.25 no.4
• /
• pp.518-527
• /
• 2020

360 VR technology is used not only in movies, but also in performing arts such as music, theater, dance, and so on due to the characteristics of immersion and presence. The technology allows the audience can be perceived a feel of participation in a story. This study is conducted an analysis of the techniques of 360 video shooting in order to find the answers of the following questionaries: how to make viewers enhance to a better understanding of a space, how to make the viewer feel comfortable ceding control of the experience, how to generate greater empathy with a 360 video. Thirty cases were analysed 360-degree videos of live performances performed on stage among 360-degree images of music performance content shared on Youtube from 2015 to 2020. The result shows that live performances are performed with the audience, so the stage shape and the layout of the audience seats are preferred to the characteristics of the performance. It was also shown that directing using a 360 VR camera was also greatly affected by the stage and audience placement. The stage is manly classified into three types, and the camera layout and characteristics mainly used are organized according to the number of 360 VR cameras, whether fixed or mobile cameras are used.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2002.10a
• /
• pp.133-137
• /
• 2002

• The Bulletin of The Korean Astronomical Society
• /
• v.30 no.1
• /
• pp.39.2-39.2
• /
• 2005

• Journal of Korea Multimedia Society
• /
• v.14 no.3
• /
• pp.356-367
• /
• 2011

In this paper, we proposed a new car engine sealing inspection system based on image processing and understanding. The car engine sealing inspection plays very important role for protecting leakage caused by inappropriate sealing, which is a crucial point for productivity of car engines. The proposed inspection system has been aimed to enhance the previously proposed sealing inspection systems based on image processing, which have high computation complexity and low performance for correctly inspecting some contamination by oil with similar color with that of sealing. Moreover, the previously proposed system has a difficulty in installing the camera system on the sealing machine. The proposed system considers a difference of images before and after sealing obtained from one static camera. By utilizing a difference of images, the proposed system shows very robust performance using a proposed simple depth checking algorithm for some contamination cases by oil with similar color with that of sealing and the total inspection system is simple and cheap to implement. According to the experiments conducted in a real car product line, the proposed inspection system shows better inspection performance and needs smaller implementation cost than three other previously proposed system working in current car sealing inspection systems.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.6
• /
• pp.1139-1145
• /
• 2014

User recognition technology, which identifies or verifies a certain individual is absolutely essential under robotic environments for intelligent services. The conventional face recognition algorithm using single distance face image as training images has a problem that face recognition rate decreases as distance increases. The face recognition algorithm using face images by actual distance as training images shows good performance but this has a problem that it requires user cooperation. This paper proposes the LDA-based long distance face recognition method which uses multiple distance face images from a zoom camera for training face images. The proposed face recognition technique generated better performance by average 7.8% than the technique using the existing single distance face image as training. Compared with the technique that used face images by distance as training, the performance fell average 8.0%. However, the proposed method has a strength that it spends less time and requires less cooperation to users when taking face images.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.6
• /
• pp.1099-1110
• /
• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Journal of Information Technology Services
• /
• v.21 no.2
• /
• pp.27-41
• /
• 2022

In a fiercely competitive environment, quality is a key factor that enables dashboard camera makers to maintain their competitive advantage. Quality affects consumer satisfaction, brand loyalty, and firm performance. Therefore, to remain competitive, it is important that manufacturers maintain product quality that meets consumer expectations. To this end, it is necessary to investigate customer preferences and product performance in terms of product quality and to properly allocate resources to improve the quality level such that the firm can maintain a competitive advantage. In this paper, we proposed the various ways in which manufacturing firms can determine which quality dimensions need improvement in order to secure competitiveness. To this end, we analyzed a case study of Urive to develop a quality improvement strategy through importance performance competitor analysis (IPCA). Urive's IPCA results showed that 14 quality dimensions, namely performance, size, price, ease of use, country of origin, manufacturer, brand, product certificate, warranty, distribution channel, market share, reliability, durability, and conformance, were not absolutely competitive compared with those of Mando, Inavi, and Finevu. In terms of color, Urive had an absolute competitive advantage over Mando, but not Inavi and Finevu. Urive's appearance was more competitive than Mando's, but not Inavi's and Finevu's. In terms of advertisement and serviceability, Urive was absolutely less competitive than Mando and Inavi, but had a competitive advantage over Finevu. Therefore, it is necessary to put resources and time as the first priority for performance, reliability, and durability, which have a large performance difference in common among the three brands. The quality dimensions in which resources and time need to be put in second place are price and ease of use, which have a large performance difference in common among the two brands.