• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.21-28
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• 2006

In a face detection system based on template matching, histogram equalization or log transform is applied to an input image for the intensity normalization and the image improvement. It is known that they are noneffective in improving an image with intensity distortion by illumination variation. In this paper, we propose an efficient image improvement method using a simple regression analysis combined with a bilateral symmetry average for images with intensity distortion by illumination variation. Experimental results show that our method delivers the detection performance better than previous methods and also remarkably reduces the number of face candidates.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.944-947
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• 2022

Due to the coronavirus pandemic, the wearing of a mask has been increasing worldwide; thus, the importance of image analysis on masked face images has become essential. Although head pose estimation can be applied to various face-related applications including driver attention, face frontalization, and gaze detection, few studies have been conducted to address the performance degradation caused by masked faces. This study proposes a new data augmentation that synthesizes the masked face, depending on the face image size and poses, which shows robust performance on BIWI benchmark dataset regardless of mask-wearing. Since the proposed scheme is not limited to the specific model, it can be utilized in various head pose estimation models.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.755-767
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• 2003

This paper proposes a robust fault-tolerant control framework for robot manipulators to maintain the required performance and achieve task completion in the presence of both partial joint failures and complete joint failures and uncertainties. In the case of a complete joint failure or free-swinging joint failure causing the complete loss of torque on a joint, a fully-actuated robot manipulator can be viewed as an underactuated robot manipulator. To detect and identify a complete actuator failure, an on-line fault detection operation is also presented. The proposed fault-tolerant control system contains a robust adaptive controller overcoming partial joint failures based on robust adaptive control methodology, an on-line fault detector detecting and identifying complete joint failures, and a robust adaptive controller overcoming partial and complete joint failures, and so eventually it can face and overcome joint failures and uncertainties. Numerical simulations are conducted to validate the proposed robust fault-tolerant control scheme.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.47-52
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• 2010

In this paper, we introduce a new approach for real-time 3D face pose discrimination based on active IR illumination from a monocular view of the camera. Under the IR illumination, the pupils appear bright. We develop algorithms for efficient and robust detection and tracking pupils in real time. Based on the geometric distortions of pupils under different face orientations, an eigen eye feature space is built based on training data that captures the relationship between 3D face orientation and the geometric features of the pupils. The 3D face pose for an input query image is subsequently classified using the eigen eye feature space. From the experiment, we obtained the range of results of discrimination from the subjects which close to the camera are from 94,67%, minimum from 100%, maximum.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1244-1248
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• 2005

In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.1-8
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• 2005

Facial analysis is used in many applications like face recognition systems, human-computer interface through head movements or facial expressions, model based coding, or virtual reality. In all these applications a very precise extraction of facial feature points are necessary. In this paper we presents a method for automatic extraction of the facial features Points such as mouth corners, eye corners, eyebrow corners. First, face region is detected by AdaBoost-based object detection algorithm. Then a combination of three kinds of feature energy for facial features are computed; valley energy, intensity energy and edge energy. After feature area are detected by searching horizontal rectangles which has high feature energy. Finally, a corner detection algorithm is applied on the end region of each feature area. Because we integrate three feature energy and the suggested estimation method for valley energy and intensity energy are adaptive to the illumination change, the proposed feature extraction method is robust under various conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.821-829
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• 2004

A face recognition has been used for verifying and authorizing valid users, but its applications have been restricted according to lighting conditions. In order to minimizing the restricted conditions, this paper proposes a new algorithm of detecting the face from the input image obtained under the irregular lighting condition. First, the proposed algorithm extracts an edge difference image from the input image where a skin color and a face contour are disappeared due to the background color or the lighting direction. In the next step, it extracts a face region using the histogram of the edge difference image and the intensity information. Using the intensity information, the face region is divided into the horizontal regions with feasible facial features. The each of horizontal regions is classified as three groups with the facial features(including eye, nose, and mouth) and the facial features are extracted using empirical properties of the facial features. Only when the facial features satisfy their topological rules, the face region is considered as a face. It has been proved by the experiments that the proposed algorithm can detect faces even when the large portion of face contour is lost due to the inadequate lighting condition or the image background color is similar to the skin color.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.109-116
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.7-12
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• 2012

In this paper, we present an effective viewpoint estimation algorithm for the Moving parallax barrier method of 3D display mobile device. Moving parallax barrier is designed to overcome the biggest problem, the limited view angle. To accomplish it, the position of the viewer's eyes or face should be estimated with strong stability and no latency. We focus on these requirements in the poor performance of mobile processors. We used a pre-processing algorithm in order to overcome the various illumination changes. And, we combined the conventional Viola-Jones face detection method and Optical-flow algorithm for robust and stable viewpoint estimation. Various computer simulations prove the effectiveness of the proposed method.