• Journal of Advanced Navigation Technology
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• v.12 no.2
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• pp.164-169
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• 2008

This paper is using motion tracking by image segmentation to monitor intruders and to confirm based on mobile the relevant information. First, detect frame in animation that film fixed area, and make use of image subtraction between two frame that adjoin, segment fixed backing and target who move. Segmental foreground object to the edge detecting the location specified by the edge of the median estimate extracted by analyzing the motion of the intruders to monitor. When a motion is detected, the detected image is transmitted by using the W AP pull basis image transmission method on the mobile client data terminal.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.453-458
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• 2002

It is not easy to analyze dynamic sports motion, but it can be done easily by using an interactive playback of the recorded motion. Everybody is able to capture a golf swing owing to the popularization of PC and digital camcorder in these days. In this study, the system that can provide golf swing analysis is selected and implemented. Furthermore, editing method that can represent motion is applied and moving object tracking algorithm that can make this profess easy is applied to provide easy golf swing analysis.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.92-102
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• 1990

A new method for determining the motion parameters (scale, rotation, translation) of 2-D image is introduced. It employs Hough transform that maps the straight lines in the input image to the points in the Hough space (HS). This method makes use of the relations between the motion of an object in input image and the translations of peak points in the HS and thus derives relating equations about motion parameters especially when scale changes are involved. The derived equations make is efficient and simple to estimate motion parameters of input image, even if the scale parameter of input image is varied. Performance of this approach on an aircraft image is provided in detail in the presence of noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.301-314
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• 1990

This paper is an attempt to use vision-pattern recognition technique to analyzation on a hidden rigid body motion. Specially shaped rod, rigidly connected to the hidden body is extended to the ouside of hiding object so that a camera may catch the motion data. Every motion can be described with translatio and rotation. But translation can be explanied with ratation with a infinitly far centroid. Motion analysis is to find the instantaneous centroid and ratation angle. With this theory jaw motion is analyzed in this paper.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.631-644
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• 2002

In this paper efficient algorithms for content-based video retrieval using motion information are proposed, including temporal scale-invariant retrieval and temporal scale-absolute retrieval. In temporal scale-invariant video retrieval, the distance transformation is performed on each trail image in database. Then, from a given que교 trail the pixel values along the query trail are added in each distance image to compute the average distance between the trails of query image and database image, since the intensity of each pixel in distance image represents the distance from that pixel to the nearest edge pixel. For temporal scale-absolute retrieval, a new coding scheme referred to as Motion Retrieval Code is proposed. This code is designed to represent object motions in the human visual sense so that the retrieval performance can be improved. The proposed coding scheme can also achieve a fast matching, since the similarity between two motion vectors can be computed by simple bit operations. The efficiencies of the proposed methods are shown by experimental results.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.657-664
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• 2003

Reliable tracking of moving humans is essential to motion estimation, video surveillance and human-computer interface. This paper presents a new approach to human motion tracking that combines appearance-based and model-based techniques. Monocular color video is processed at both pixel level and object level. At the pixel level, a Gaussian mixture model is used to train and classily individual pixel colors. At the object level, a 3D human body model projected on a 2D image plane is used to fit the image data. Our method does not use inverse kinematics due to the singularity problem. While many others use stochastic sampling for model-based motion tracking, our method is purely dependent on nonlinear programming. We convert the human motion tracking problem into a nonlinear programming problem. A cost function for parameter optimization is used to estimate the degree of the overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. Our method is used to recognize various human motions. Motion tracking results from video sequences are very encouraging.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1203-1210
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• 2007

Robots have begun to perform various tasks on replacing the human in the daily life such as cleaning, entertainments etc. In order to accomplish the effective performance of intricate and precise tasks, robot hand must have special capabilities, such as decision making in given condition, autonomy in unknown situation and stable manipulation of object. In this study, we addresses the development of a 3-fingered humanoid robot hand system. We execute static analysis, vibration analysis and flexible dynamics to reserve stability at the design. Grasp motion of the finger uses a linear actuator and gears. Motion can be distinguished into four parts depending on the grasping thin paper, sphere, and column. In each motion, we compare the displacement of the case to be rigid with the case to be flexible. As a result, manufactured and feasibility of the robot hand is validated through preliminary experiments.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.61-67
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• 1999

A laser Doppler vibrometer based on the laser heterodyne interferometry is employed to measure the vibration velocity of vibrating objects. In this paper, we propose a real time analog signal processor of a laser Doppler vibrometer to reduce the degradation of Doppler signals mainly caused by environmental noises. In the proposed real time signal processor of an laser Doppler vibrometer, a pre-processor and a logical motion direction detector are designed to reduce the detection errors of the object motion direction. Also, a noise detection and rejection circuit is designed to reject the unfiltered noises.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.227-234
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• 2000

The human sensibility caused by the motion of an object grasped by a human operator is defined as kinesthetic sense of arm. Due to nonlinearity and ambiguity of human sense, there is no absolute standard for quantification of kinesthetic sense. In this research, a so-called 2-dimensional arm motion generator is developed to present various mechanical impedance (i.e., stiffness or damping) characteristics to a human arm. The kinesthetic words representing arm kinesthetic sense are selected and then the subject's satisfaction levels on these words for given impedance values are measured and processed by the SD method and factor analysis. In addition, the quantification method using neural network is proposed to take into account the individual difference between the mean sensibility and each subject's sensibility. Through this proposed algorithm, the sensibility of human motion described qualitatively can be converted into engineering data ensuring objectivity, reproducibility, and universality.