• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3136-3150
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• 2015

A vision-based 3D tracking of articulated human hand is one of the major issues in the applications of human computer interactions and understanding the control of robot hand. This paper presents an improved approach for tracking and recovering the 3D position and orientation of a human hand using the Kinect sensor. The basic idea of the proposed method is to solve an optimization problem that minimizes the discrepancy in 3D shape between an actual hand observed by Kinect and a hypothesized 3D hand model. Since each of the 3D hand pose has 23 degrees of freedom, the hand articulation tracking needs computational excessive burden in minimizing the 3D shape discrepancy between an observed hand and a 3D hand model. For this, we first created a 3D hand model which represents the hand with 17 different parts. Secondly, Random Forest classifier was trained on the synthetic depth images generated by animating the developed 3D hand model, which was then used for Haar-like feature-based classification rather than performing per-pixel classification. Classification results were used for estimating the joint positions for the hand skeleton. Through the experiment, we were able to prove that the proposed method showed improvement rates in hand part recognition and a performance of 20-30 fps. The results confirmed its practical use in classifying hand area and successfully tracked and recovered the 3D hand pose in a real time fashion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.553-563
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• 1996

Detecting edges is one of issues with essentialimprotance in the area of image analysis. An edge in an image is a boundary or contour at which a significant change occurs in image intensity. Edge detection has been studied in many addlications such as imagesegmentation, robot vision, and image compression. In this paper, we propose an automatic threshold selection scheme for edge detection and show its application to noise elimination. The scheme suggested here applied statistical properties of the noise estimated from a noisy image to threshold selection. Since a selected threshold value in the scheme depends on not the characgreistic of an orginal image but the statistical feature of added noise, we can remove ad-hoc manners used for selecting the threshold value as well as decide the value theoretically. Furthermore, that shceme can reduce the number of edge pixels either generated or lost by noise. an application of the scheme to noise elimination is shown here. Noise in the input image can be eliminated with considering the direction of each edge pixedl on the edge map obtained by applying the threshold selection scheme proposed in this paper. Achieving significantly improved results in terms of SNR as well as subjective quality, we can claim that the suggested method works well.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.48-56
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• 2014

In robotic surgery, a surgeon checks only a surgical site of patient in the progress of surgery by vision and sound information. In order to solve this limited information, the haptic function is necessary. And haptic surgical robot is also necessary to design a haptic master device. The master device for laparoscope operation with cable-conduit was developed in previous research to give haptic function. It suggested a possibility of developing a master device by using the cable-conduit. However, it is very inconvenient to use. Therefore, this paper suggests a new mechanism design structure to solve the problems of the previous work by new forming a new master device. And it has proved that it's usability is better than previous one. Furthermore it has also experimented and analyzed that a backlash of new master device is compensated by smooth backlash inverse algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.39-46
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• 2006

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.669-670
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• 2016

In this study, we developed an application that athletic leaders can refer to the map data, separated by a hot zone results of student athletes (Hot Zone) and cold zones (Cold Zone). The sport developed in this study is basketball. Athletic club's coachs can analyze a high probability of a student scoring players can use them to further improve training results. And student athletes also can through the accumulated data to identify their strengths and weaknesses expect motivation and performance enhancement, and accordingly expected to further study.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3037-3040
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• 2000

Real-Time object tracking has emerged as an important component in several application areas including machine vision. surveillance. Human-Computer Interaction. image-based control. and so on. And there has been developed various algorithms for a long time. But in many cases. they have showed limited results under uncontrolled situation such as illumination changes or cluttered background. In this paper. we present a novel. computationally efficient algorithm for tracking human face robustly under illumination changes and cluttered backgrounds. Previous algorithms usually defines color model as a 2D membership function in a color space without consideration for illumination changes. Our new algorithm developed here. however. constructs a 3D color model by analysing plenty of images acquired under various illumination conditions. The algorithm described is applied to a mobile head-eye robot and experimented under various uncontrolled environments. It can track an human face more than 100 frames per second excluding image acquisition time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1034-1037
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• 2015

In recent years in the field of robotics, various methods have been developed to create an intimate relationship between people and robots. These methods include speech, vision, and biometrics recognition as well as gesture-based interaction. These recognition technologies are used in various wearable devices, smartphones and other electric devices for convenience. Among these technologies, gesture recognition is the most commonly used and appropriate technology for wearable devices. Gesture recognition can be classified as contact or noncontact gesture recognition. This paper proposes contact gesture recognition with IMU and EMG sensors by using the hidden Markov model (HMM) twice. Several simple behaviors make main gestures through the one-stage HMM. It is equal to the Hidden Markov model process, which is well known for pattern recognition. Additionally, the sequence of the main gestures, which comes from the one-stage HMM, creates some higher-order gestures through the two-stage HMM. In this way, more natural and intelligent gestures can be implemented through simple gestures. This advanced process can play a larger role in gesture recognition-based UX for many wearable and smart devices.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.519-524
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• 2009

This paper describes a new sensor system for 3D environment perception using stereo structured infrared light sources and a camera. Environment and obstacle sensing is the key issue for mobile robot localization and navigation. Laser scanners and infrared scanners cover $180^{\circ}$ and are accurate but too expensive. Those sensors use rotating light beams so that the range measurements are constrained on a plane. 3D measurements are much more useful in many ways for obstacle detection, map building and localization. Stereo vision is very common way of getting the depth information of 3D environment. However, it requires that the correspondence should be clearly identified and it also heavily depends on the light condition of the environment. Instead of using stereo camera, monocular camera and two projected infrared light sources are used in order to reduce the effects of the ambient light while getting 3D depth map. Modeling of the projected light pattern enabled precise estimation of the range. Two successive captures of the image with left and right infrared light projection provide several benefits, which include wider area of depth measurement, higher spatial resolution and the visibility perception.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.670-672
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• 2005

본 논문은 비전을 기반으로 한 감정인식 로봇에 관한 논문이다. 피부스킨칼라와 얼굴의 기하학적 정보를 이용한 얼굴검출과 감정인식 알고리즘을 제안하고, 개발한 로봇 시스템을 설명한다. 얼굴 검출은 RGB 칼라 공간을 CIElab칼라 공간으로 변환하여, 피부스킨 후보영역을 추출하고, Face Filter로 얼굴의 기하학적 상관관계를 통하여 얼굴을 검출한다. 기하학적인 특징을 이용하여 눈, 코, 입의 위치를 판별하여 표정 인식의 기본 데이터로 활용한다. 눈썹과 입의 영역에 감정 인식 윈도우를 적용하여, 윈도우 내에서의 픽셀값의 변화와 크기의 변화로 감정인식의 특징 칼을 추출한다. 추출된 값은 실험에 의해서 미리 구해진 샘플과 비교를 통해 강정을 표현하고, 표현된 감정은 Serial Communication을 통하여 로봇에 전달되고, 감정 데이터를 받은 얼굴에 장착되어 있는 모터를 통해 표정을 표현한다.