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Goal-Posture-Determination of a Steerable Mobile Robot for Active Information Display
이정엄,이종호,김동원 아이씨티플랫폼학회 2018 JOURNAL OF PLATFORM TECHNOLOGY Vol.6 No.4
A projection-based active information display system was proposed. The proposed system is based on Intelligent Space and a steerable projector mounted mobile robot which is called Ubiquitous Display (UD). In order to transfer visual information for a human in the Intelligent Space, the UD projects a certain shape of an image with a fixed size. Due to redundancy of degree of freedom (DOF), there are lots of situations to project a same shape and size of the image on a surface. In this paper, we describe a method to determine a goal posture of the UD. Here, the goal posture is the most efficient position and orientation of the UD so as to project visual information and it is determined by the Intelligent Space. To verify the proposed method, simulation and demonstration are carried out.
Human and Robot Tracking Using Histogram of Oriented Gradient Feature
이정엄,이종호,김동원 아이씨티플랫폼학회 2018 JOURNAL OF PLATFORM TECHNOLOGY Vol.6 No.4
This paper describes a real-time human and robot tracking method in Intelligent Space with multicameranetworks. The proposed method detects candidates for humans and robots by using thehistogram of oriented gradients (HOG) feature in an image. To classify humans and robots from thecandidates in real time, we apply cascaded structure to constructing a strong classifier which consistsof many weak classifiers as follows: a linear support vector machine (SVM) and a radial-basis function(RBF) SVM. By using the multiple view geometry, the method estimates the 3D position of humans androbots from their 2D coordinates on image coordinate system, and tracks their positions by usingstochastic approach. To test the performance of the method, humans and robots are asked to moveaccording to given rectangular and circular paths. Experimental results show that the proposedmethod is able to reduce the localization error and be good for a practical application of humancenteredservices in the Intelligent Space.
이정엄(Jeong-Eom Lee),이석주(Seok-Joo Lee),박귀태(Gwi- Tae Park) 한국자동차공학회 2006 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
For a vision-based occupant s pose recognition system, this paper presents a new algorithm that can detect the head of the car occupant. Head detection is necessary for occupant's pose recognition in the car, since the position of occupant's head provides valuable information, such as his pose, size, position, and so on. We use the head-shoulder models and support vector machines. Given the variable illumination conditions within the car, the color information for detecting the head (or face) is not sufficient. Our method is based upon using only the grey image, since the infrared illumination could be utilized in the night. Although it is known that SVM could be useful for detection the face, such method can be slower when the size of the training set images is increased to cover diverse pose and size variation of the face. Since the contours in our study are lighter than the conventional face images in terms of SVM processing, it fits to the embedded system installed in the car. Results suggest that the head-shoulder contour model and support vector machines for detection the occupant's head could find a few useful applications.
위상차 현미경 영상 내 푸리에 묘사자를 이용한 암세포 형태별 분류
강미선,이정엄,김혜련,김명희,Kang, Mi-Sun,Lee, Jeong-Eom,Kim, Hye-Ryun,Kim, Myoung-Hee 대한의용생체공학회 2012 의공학회지 Vol.33 No.4
Tumor cell morphology is closely related to its migratory behaviors. An active tumor cell has a highly irregular shape, whereas a spherical cell is inactive. Thus, quantitative analysis of cell features is crucial to determine tumor malignancy or to test the efficacy of anticancer treatment. We use 3D time-lapse phase-contrast microscopy to analyze single cell morphology because it enables to observe long-term activity of living cells without photobleaching and phototoxicity, which is common in other fluorescence-labeled microscopy. Despite this advantage, there are image-level drawbacks to phase-contrast microscopy, such as local light effect and contrast interference ring. Therefore, we first corrected for non-uniform illumination artifacts and then we use intensity distribution information to detect cell boundary. In phase contrast microscopy image, cell is normally appeared as dark region surrounded by bright halo ring. Due to halo artifact is minimal around the cell body and has non-symmetric diffusion pattern, we calculate cross sectional plane which intersects center of each cell and orthogonal to first principal axis. Then, we extract dark cell region by analyzing intensity profile curve considering local bright peak as halo area. Finally, we calculated the Fourier descriptor that morphological characteristics of cell to classify tumor cells into active and inactive groups. We validated classification accuracy by comparing our findings with manually obtained results.
김주형,박귀태,이정엄,이주호 제어·로봇·시스템학회 2012 International Journal of Control, Automation, and Vol.10 No.4
Networked mobile robots are able to determine their poses (i.e., position and orientation) with the help of a well-configured environment with distributed sensors. Before localizing the mobile robots using distributed sensors, the environment has to have information on each of the robots’ prior knowledge. Consequently, if the environment does not have information on the prior knowledge of a certain mobile robot then it will not determine its current pose. To solve this restriction, as a preprocessing step for indoor localization, we propose a motion-based identification of multiple mobile robots using trajectory analysis. The proposed system identifies the robots by establishing the relation between their identities and their positions, which are estimated from their trajectories related to each of the paths generated as designated signs. The primary feature of the proposed system is the fact that networked mobile robots are quickly and simultaneously able to determine their poses in well-configured environments. Experimental results show that our proposed system simultaneously identifies multiple mobile robots, and approximately estimates each of their poses as an initial state for autonomous localization.