• The Journal of the Korea Contents Association
• /
• v.8 no.4
• /
• pp.273-284
• /
• 2008

Movements are a critical ability to young children's whole development, including physical, social/emotional, and cognitive development. This paper proposes the method to estimate movements suitable for young children's body conditions. The proposed method extracts a silhouette in each frame of videos that are obtained by deploying two video cameras by compensating illuminations, removing background and conducting morphology operations. And we extract silhouette feature values: an area, the ratio of length to width, the lowest foot position, and 7 Hu moments. Also, the area and movements of sub-area are used as local features. For motion estimation, we used probability propagation of the features extracted from the front and side frames. The proposed estimation algorithm is demonstrated for seven movements, walking, jumping, hopping, bending, stretching, balancing, and turning.

• Journal of Broadcast Engineering
• /
• v.1 no.2
• /
• pp.176-187
• /
• 1996

This paper deals with the accurate estimation of 3- D pose (position and orientation) of a moving object with reference to the world frame (or robot base frame), based on a sequence of stereo images taken by cameras mounted on the end - effector of a robot manipulator. This work is an extension of the previous work[1]. Emphasis is given to the 3-D pose estimation relative to the world (or robot base) frame under the presence of not only the measurement noise in 2 - D images[ 1] but also the camera position errors due to the random noise involved in joint angles of a robot manipulator. To this end, a new set of discrete linear Kalman filter equations is derived, based on the following: 1) the orientation error of the object frame due to measurement noise in 2 - D images is modeled with reference to the camera frame by analyzing the noise propagation through 3- D reconstruction; 2) an extended Jacobian matrix is formulated by combining the result of 1) and the orientation error of the end-effector frame due to joint angle errors through robot differential kinematics; and 3) the rotational motion of an object, which is nonlinear in nature, is linearized based on quaternions. Motion parameters are computed from the estimated quaternions based on the iterated least-squares method. Simulation results show the significant reduction of estimation errors and also demonstrate an accurate convergence of the actual motion parameters to the true values.

• 전자공학회논문지 IE
• /
• v.47 no.2
• /
• pp.38-46
• /
• 2010

In this paper, an autonomous surveillance-tracking system for Workers monitoring basing on the stereo vision scheme is proposed. That is, analysing the characteristics of the cross-axis camera system through some experiments, a optimized stereo vision system is constructed and using this system an intelligent worker surveillance-tracking system is implemented, in which a target worker moving through the environments can be detected and tracked, and its resultant stereo location coordinates and moving trajectory in the world space also can be extracted. From some experiments on moving target surveillance-tracking, it is analyzed that the target's center location after being tracked is kept to be very low error ratio of 1.82%, 1.11% on average in the horizontal and vertical directions, respectively. And, the error ratio between the calculation and measurement values of the 3D location coordinates of the target person is found to be very low value of 2.5% for the test scenario on average. Accordingly, in this paper, a possibility of practical implementation of the intelligent stereo surveillance system for real-time tracking of a target worker moving through the environments and robust detection of the target's 3D location coordinates and moving trajectory in the real world is finally suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.721-723
• /
• 2007

Recently, the size and location of the acquired container image while the container is loading and unloading in Harbors is not fixed. And it is difficult to get a good image for recognition because of the variation of external environment as those the size of container and where the yard-tractor stop is. In this paper, we estimate where the container ISO-code set is using Top-hat transform from realtime images and get an image to recognize container ISO-code using PAN/TILT/ZOOM camera. We extract the container ISO-code using Top-hat transform and Histogram projection. After binarization, we extract each character from complex background using labeling. We use BP(Backpropagation Network) to recognize extracted characters.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.5
• /
• pp.61-68
• /
• 2021

In this paper, we propose an edge computing-based exercise data collection device that can be provided for exercise rehabilitation services. In the existing cloud computing method, when the number of users increases, the throughput of the data center increases, causing a lot of delay. In this paper, we design and implement a device that measures and estimates the position of keypoints of body joints for movement information collected by a 3D camera from the user's side using edge computing and transmits them to the server. This can build a seamless information collection environment without load on the cloud system. The results of this study can be utilized in a personalized rehabilitation exercise coaching system through IoT and edge computing technologies for various users who want exercise rehabilitation.

• The Journal of the Korea Contents Association
• /
• v.7 no.11
• /
• pp.34-42
• /
• 2007

In this paper, we propose a staff-line detection and removal algorithm from a music score image obtained by a mobile phone camera. As a preprocessing technique to recognize a music score image, staff-line detection and removal should be efficiently applied to the skewed or curved images. The proposed method detects a staff-line by dividing a staff according to the degree of distortion. The number of division is calculated by dividing a staff repletely until an average of differences of y coordinates in every divided position is smaller than a threshold. Therefore, the number of division can be adaptively estimated according to the degree of the distortion. For an experiment, we make various kinds of images by rotating one from $1^{\circ}\;to\;3^{\circ}$ or curving slightly upward. The results show that the proposed method performed well on the experiment images.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.37 no.8
• /
• pp.11-23
• /
• 2000

Head-eye calibration is a process for estimating the unknown orientation and position of a camera with respect to a mobile platform, such as a robot wrist. We present a new head-eye calibration technique which can be applied for platforms with rather limited motion capability In particular, the proposed calibration technique can be applied to find the relative orientation of a camera mounted on a linear translation platform which does not have rotation capability. The algorithm find the rotation using a calibration data obtained from pure Translation of a camera along two different axes We have derived a calibration algorithm exploiting the rectification technique in such a way that the rectified images should satisfy the epipolar constraint. We present the calibration procedure for both the rotation and the translation components of a camera relative to the platform coordinates. The efficacy of the algorithm is demonstrated through simulations and real experiments.

• Journal of IKEEE
• /
• v.23 no.2
• /
• pp.642-651
• /
• 2019

One of the most important research topics on intelligent transportation systems in recent years is detecting and recognizing a license plate. The license plate has a unique identification data on vehicle information. The existing vehicle traffic control system is based on a stop and uses a loop coil as a method of vehicle entrance/exit recognition. The method has the disadvantage of causing traffic jams and rising maintenance costs. We propose to exploit differential image of camera background instead of loop coil as an entrance/exit recognition method of vehicles. After entrance/exit recognition, we detect the candidate images of license plate using the morphological characteristics. The license plate can finally be detected using SVM(Support Vector Machine). Letter and numbers of the detected license plate are recognized using CNN(Convolutional Neural Network). The experimental results show that the proposed algorithm has a higher recognition rate than the existing license plate recognition algorithm.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.511-513
• /
• 2004

Camera Calibration should certain)y be achieved to take an accurate measurement using image system. Calibration is to prove the relation between an measurement object and camera and to estimate twelve internal and external parameters. In this paper, we suggest that an algorithm should estimate the external parameters from the road image and use a vanishing point's character from parallel straight lines in a space. also, we use Hough Transform to estimate an accurate vanishing point. Hough Transform has one of the advantages which is an application for each road environment. we assume a variety of environments to prove the usability of a suggested algorithm and show simulation results with a computer.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.9
• /
• pp.1416-1423
• /
• 2017

Lane detection technology is one of the most important issues on car safety and self-driving capability of autonomous vehicle. This paper introduces an accurate lane detection scheme based on OCC(Optical Camera Communication) for moving vehicles. For lane detection of moving vehicles, the streetlights and the front camera of the vehicle were used for a transmitter and a receiver, respectively. Based on the angle information of multiple streetlights in a captured image, the distance from sidewalk can be calculated using non-linear regression analysis. Simulation results show that the proposed scheme shows robust performance of accurate lane detection.