• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.749-752
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• 1998

Recognizing a human part becomes very important for applications which are based on the interaction between computers and their users. In this paper, we design and implement a system which recognizes and tracks a human head using a sequence of images. Difference images are used to easily extract feature vectors from images with very complex backgrounds. A human bhead is represented with an ellipse and recognized by searching for a maximum value from preprocessed gradient images. The method is developed by considering the fact that the tracking system should be real-time. The designed system not only shows an excellent performance for the normal up-right position of the head, but also for the cases of 360.deg. rotated head position, occluded images of heads, and tilted head positions.

• Journal of the Korea Computer Industry Society
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• v.9 no.3
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• pp.105-114
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• 2008

We present an eye tracking system using a low cost 3D CMOS imager for 3D displays that ensures a correct auto stereoscopic view of position- dependent stereoscopic 3D images. The tracker is capable of segmenting the foreground objects (viewer) from background objects using their relative distance from the camera. The tracker is a novel 3D CMOS Image Sensor based on Time of Flight (TOF) principle using innovating photon gating techniques. The basic feature incorporates real time depth imaging by capturing the shape of a light-pulse front as it is reflected from a three dimensional object. The basic architecture and main building blocks of a real time depth CMOS pixel are described. For this application, we use a stereoscopic type of display using parallax barrier elements that is described as well.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.11-14
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• 2000

In this paper, we propose a fast and practical head pose estimation scheme fur eye-head controlled human computer interface with non-constrained background. The method we propose uses complete graph matching from thresholded images and the two blocks showing the greatest similarity are selected as eyes, we also locate mouth and nostrils in turn using the eye location information and size information. The average computing time of the image(360*240) is within 0.2(sec) and we employ template matching method using angles between facial features for head pose estimation. It has been tested on several sequential facial images with different illuminating conditions and varied head poses, It returned quite a satisfactory performance in both speed and accuracy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.119-126
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• 2019

As interest in augmented reality has increased recently, attempts have been made to incorporate augmented reality into various fields. In implementing augmented reality, the method by which markers are used is to extract feature points of markers to recognize 3D coordinates and, in some cases, it is necessary to recognize multiple markers simultaneously. Therefore, this paper proposes optimization methods for recognising multiple markers at the same time. Unity 3D and augmented reality library Vuforia are used to implement the experimental environment. The augmented reality program produced was implemented in an application form and tested using a mobile camera. We looked for optimization methods for manufacturing markers directly and for recognizing multiple markers through changes in the experimental environment. The results of the experiment can provide a higher recognition rate in an environment where multiple marker recognition is required later.

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.97-101
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• 2019

Understanding and classification of the human's emotion play an important tasks in interacting with human and machine communication systems. This paper proposes a novel emotion recognition method by extracting facial keypoints, which is able to understand and classify the human emotion, using active Appearance Model and the proposed classification model of the facial features. The existing appearance model scheme takes an expression of variations, which is calculated by the proposed classification model according to the change of human facial expression. The proposed method classifies four basic emotions (normal, happy, sad and angry). To evaluate the performance of the proposed method, we assess the ratio of success with common datasets, and we achieve the best 93% accuracy, average 82.2% in facial emotion recognition. The results show that the proposed method effectively performed well over the emotion recognition, compared to the existing schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1816-1825
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• 2022

In this paper, we propose a new approach for tracking each human in a surveillance camera network with various resolution cameras. When tracking human on multiple non-overlapping cameras, the traditional appearance features are easily affected by various camera viewing conditions. To overcome this limitation, the proposed system utilizes facial information along with appearance information. In general, human images captured by the surveillance camera are often low resolution, so it is necessary to be able to extract useful features even from low-resolution faces to facilitate tracking. In the proposed tracking scheme, texture-based face descriptor is exploited to extract features from detected face after face frontalization. In addition, when the size of the face captured by the surveillance camera is very small, a super-resolution technique that enlarges the face is also exploited. The experimental results on the public benchmark Dana36 dataset show promising performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.835-854
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• 2012

In this paper, we propose a novel positioning system for indoor navigation which helps a user navigate easily to desired destinations in an unfamiliar indoor environment using his mobile phone. The system requires only the user's mobile phone with its basic equipped sensors such as a camera and a compass. The system tracks user's positions and orientations using a vision-based approach that utilizes $360^{\circ}$ panoramic images captured in the environment. To improve the robustness of the vision-based method, we exploit a digital compass that is widely installed on modern mobile phones. This hybrid solution outperforms existing mobile phone positioning methods by reducing the error of position estimation to around 0.7 meters. In addition, to enable the proposed system working independently on mobile phone without the requirement of additional hardware or external infrastructure, we employ a modified version of a fast and robust feature matching scheme using Histogrammed Intensity Patch. The experiments show that the proposed positioning system achieves good performance while running on a mobile phone with a responding time of around 1 second.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1650-1654
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• 2004

This paper presents how it is effective to use many features for improving the speed and the accuracy of the visual servo systems. Some rank conditions which relate the image Jacobian and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm Robot manipulator made in Samsung Electronic Co. Ltd.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.778-782
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• 2003

This paper presents how it is effective to use many features for improving the speed and the accuracy of the visual servo systems. Some rank conditions which relate the image Jacobian and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm Robot manipulator made in Samsung Electronic Co. Ltd.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.435-437
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• 2012

본 논문에서는 반복적인 베이시안 모델을 이용한 특징점 기반 객체 추적 방법을 제안한다. 제안하는 방법은 특징점 추정 오류를 최소화하고, 추적하는 객체에 해당되는 특징점들만을 선택함으로써, 최적의 특징점들을 이용하여 변환 행렬을 추정한다. 특징점 추정 오류는 Census transform과 해밍 거리를 이용하여 최소화하고, 외곽 특징점(outlier feature)를 제거하기 위하여 반복적인 베이시안 모델을 사용한다. 보행자와 차량등을 이용한 실험 결과, 제안한 방법이 기존 방법에 비하여 좀 더 우수한 성능을 보여준다.