• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.2
• /
• pp.456-463
• /
• 2004

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tacking methodology that works under variable and realistic lighting conditions. Based on combining the bright-Pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils ale not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tacking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Journal of Korea Multimedia Society
• /
• v.19 no.8
• /
• pp.1225-1235
• /
• 2016

This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.3
• /
• pp.198-204
• /
• 2007

In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.6
• /
• pp.1156-1161
• /
• 2007

Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• Korean Journal of Remote Sensing
• /
• v.17 no.4
• /
• pp.319-334
• /
• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Journal of Korea Multimedia Society
• /
• v.24 no.7
• /
• pp.880-889
• /
• 2021

In everyday life, recognizing people's emotions from their frames is essential and is a popular research domain in the area of computer vision. Visual emotion has a severe class imbalance in which most of the data are distributed in specific categories. The existing methods do not consider class imbalance and used accuracy as the performance metric, which is not suitable for evaluating the performance of the imbalanced dataset. Therefore, we proposed a method for recognizing visual emotion using balanced data augmentation to address the class imbalance. The proposed method generates a balanced dataset by adopting the random over-sampling and image transformation methods. Also, the proposed method uses the Focal loss as a loss function, which can mitigate the class imbalance by down weighting the well-classified samples. EfficientNet, which is the state-of-the-art method for image classification is used to recognize visual emotion. We compare the performance of the proposed method with that of conventional methods by using a public dataset. The experimental results show that the proposed method increases the F1 score by 40% compared with the method without data augmentation, mitigating class imbalance without loss of classification accuracy.

• Journal of Industrial Convergence
• /
• v.2 no.2
• /
• pp.3-30
• /
• 2004

This study intends to closely examine an evaluation of effectiveness of the HRM associated with interactions among employees(I), purpose recognition(P), role feedbacks(R), and motivative compensation(M). The following is a summary of the results of this research: From the study of the actual situation of the human resource management by the Korean firms, it appeared that the form of existence of vision systems possessed the form of having been written as documents and co-shared. And, although, in the area of motivation endowment and feedbacks, the level of motivation endowment regarding the comprising member by those in charge of departments and the level of reflection of the company's personnel policies in the execution of work by the departments were ordinary, the level of presenting the opinion of the departments regarding the company's personnel policies was shown to be low. And, the decisive elements of wages and the compensation standard were in the order of performance basis and long service. Also, it was analyzed that the leadership style of the CEO is the most important element that influences human resource management policies. And, it was analyzed that in the evaluation of the human resource management area the roles regarding evaluation and compensation, especially, the mutual interactions of the comprising members, feedbacks, and improvement activities are inadequate. And the managerial implications are discussed.

• Journal of the Society of Naval Architects of Korea
• /
• v.56 no.1
• /
• pp.66-74
• /
• 2019

In the field of shipbuilding design, the use of 3D CAD is becoming commonplace, and most of the large shipyards are conducting 3D design. However at the production site, workers are still working on 2D drawings rather than 3D models. This tendency is even worse in small-scale shipyards and block manufacturing shops. Particularly, in a manufacturing shop that is engaged in the outsourcing of blocks, it may not be possible to provide 3D model. However, the demand for 3D models in the production field is steadily increasing. Therefore, it would be helpful if 3D model could be generated from a 2D drawing. In this paper, we propose a method to extract template and unfolded surface shape information from shell template offset drawing using computer vision technology. Also a 3D surface model was reconstructed and visualized from the extracted information. The result of this study is thought to be helpful in the work environment where 3D model information can not be obtained.

• Journal of Korea Multimedia Society
• /
• v.22 no.9
• /
• pp.1000-1010
• /
• 2019

Image semantic segmentation and dehazing are key tasks in the computer vision. In recent years, researches in both tasks have achieved substantial improvements in performance with the development of Convolutional Neural Network (CNN). However, most of the previous works for semantic segmentation assume the images are captured in clear weather and show degraded performance under hazy images with low contrast and faded color. Meanwhile, dehazing aims to recover clear image given observed hazy image, which is an ill-posed problem and can be alleviated with additional information about the image. In this work, we propose a deep multi-task network for simultaneous semantic segmentation and dehazing. The proposed network takes single haze image as input and predicts dense semantic segmentation map and clear image. The visual information getting refined during the dehazing process can help the recognition task of semantic segmentation. On the other hand, semantic features obtained during the semantic segmentation process can provide cues for color priors for objects, which can help dehazing process. Experimental results demonstrate the effectiveness of the proposed multi-task approach, showing improved performance compared to the separate networks.

• Journal of Korea Multimedia Society
• /
• v.24 no.2
• /
• pp.267-273
• /
• 2021

Recently, the small-size mobile robots with remote-control are rapidly growth which market of mobile is increased in the world. Especially, the smart-phones are widely used for interface device in the small size of a mobile robot. The research goal is control system design which is applied to miniaturization of a mobile robot using smart-phone and it can be confirmed performance for designed system. Meanwhile, the fabrication of mini-mobile robot can also be remote-control operation through the WIFI performance of a smart-phone. The smart-phone is used to remote-control for robot operation which control data transmit to robot via the WIFI network. To drive the robot, we can observe by the smart-phone screen and it can easily adjust the robot drive condition and direction by smart-phone button. Consequentially, there was no malfunction and images were printed out well. However, in drive, because of blind spot, robot was bumped into obstacle. Therefore, the additional test is necessary to sensor for blind spot which sensor can be equipment to mobile robot. In addition, the experiment with robot object recognition is needed.