• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.54-59
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• 2005

The cylindrical object are widely used as mechanical parts in the manufacturing process. In order to handling those objects using a robot or an automated machine automatically, the pose of the object must be known. The pose can be described by two rotation angles; one angle about the x axis and the other about the y axis. In the many previous researches these angles were obtained by the computationally intensive algorithm, that is, fitting the data as a polynomial and doing pseudo inverse. So that, this method required high performance microprocessor. In this paper in order to avoid complex computation, a new method based on a genetic algorithm is proposed and analyzed through a series of simulations. This algorithm utilized the geometry of the cylindrical shape. The simulation results show that this method find the pose angles very well In most cases, but the computation time is randomly changed because the genetic algorithm is basically one of the random search method.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.4
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• pp.607-616
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• 2014

Face recognition is a big challenge in surveillance system since different rotation angles of the face make the difficulty to recognize the face of the same person. This paper proposes a novel method to recognize face with different head poses by using 3D information of the face. Firstly, head pose estimation (estimation of different head pose angles) is accomplished by the POSIT algorithm. Then, 3D face image data is constructed by using head pose estimation. After that, 2D image and the constructed 3D face matching is performed. Face verification is accomplished by using commercial face recognition SDK. Performance evaluation of the proposed method indicates that the error range of head pose estimation is below 10 degree and the matching rate is about 95%.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.337-345
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• 2023

In this study, we formulated a method that evaluates Taekwondo Poomsae performance using a series of choreographed training movements. Despite recent achievements in 3D human pose estimation (HPE) performance, the analysis of human actions remains challenging. In particular, Taekwondo Poomsae action analysis is challenging owing to the absence of time synchronization data and necessity to compare postures, rather than directly relying on joint locations owing to differences in human shapes. To address these challenges, we first decomposed human joint representation into joint rotation (posture) and limb length (body shape), then synchronized a comparison between test and reference pose sequences using DTW (dynamic time warping), and finally compared pose angles for each joint. Experimental results demonstrate that our method successfully synchronizes test action sequences with the reference sequence and reflects a considerable gap in performance between practitioners and professionals. Thus, our method can detect incorrect poses and help practitioners improve accuracy, balance, and speed of movement.

• Smart Structures and Systems
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• v.18 no.4
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• pp.801-818
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• 2016

To estimate structural displacement, a visually servoed paired structured light system (ViSP) was proposed in previous studies. The ViSP is composed of two sides facing each other, each with one or two laser pointers, a 2-DOF manipulator, a camera, and a screen. By calculating the positions of the laser beams projected onto the screens and rotation angles of the manipulators, relative 6-DOF displacement between two sides can be estimated. Although the performance of the system has been verified through various simulations and experimental tests, it has a limitation that the accuracy of the displacement measurement depends on the alignment of the laser pointers. In deriving the kinematic equation of the ViSP, the laser pointers were assumed to be installed perfectly normal to the same side screen. In reality, however, this is very difficult to achieve due to installation errors. In other words, the pose of laser pointers should be calibrated carefully before measuring the displacement. To calibrate the initial pose of the laser pointers, a specially designed jig device is made and employed. Experimental tests have been performed to validate the performance of the proposed calibration method and the results show that the estimated displacement with the initial pose calibration increases the accuracy of the 6-DOF displacement estimation.

• 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.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.396-398
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• 2009

Scoliosis is a three-dimensional deformity caused by lateral curvature of the spine. The existing braces used to correct the posture were some drawbacks such as inconvenience, tightness as well as unfitness to wear. In this study, we devised a posture guidance system in order to monitor a posture continuously and lead to pose correctly and a new method fur measuring a Cobb's angle value in third dimension based on two 3-axis accelerometers. As a result, the correlation coefficients between desired and measured angles were and standard error between desired and measured angles were 0.99, 1.32(x-axis), 0.99 and 1.10(y-axis), respectively. The devised system showed good potential for the optimal posture guide and an early detection of scoliosis.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.535-546
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• 2019

Recently, there have been a lot of researches on the whole face replacement system, but it is not easy to obtain stable results due to various attitudes, angles and facial diversity. To produce a natural synthesis result when replacing the face shown in the video image, technologies such as face area detection, feature extraction, face alignment, face area segmentation, 3D attitude adjustment and facial transposition should all operate at a precise level. And each technology must be able to be interdependently combined. The results of our analysis show that the difficulty of implementing the technology and contribution to the system in facial replacement technology has increased in facial feature point extraction and facial alignment technology. On the other hand, the difficulty of the facial transposition technique and the three-dimensional posture adjustment technique were low, but showed the need for development. In this paper, we propose four facial replacement models such as 2-D Faceswap, OpenPose, Deekfake, and Cycle GAN, which are suitable for the Cox platform. These models have the following features; i.e. these models include a suitable model for front face pose image conversion, face pose image with active body movement, and face movement with right and left side by 15 degrees, Generative Adversarial Network.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.354-362
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• 2010

This paper proposes a new method for a hierarchical analysis of human gait by dividing the motion into gait direction and gait posture using the tool of dynamic Bayesian network. Based on Factorial HMM (FHMM), which is a type of DBN, we design the Gait Motion Decoder (GMD) in a circular architecture of state space, which fits nicely to human walking behavior. Most previous studies focused on human identification and were limited in certain viewing angles and forwent modeling of the walking action. But this work makes an explicit and separate modeling of pedestrian pose and posture to recognize gait direction and detect orientation change. Experimental results showed 96.5% in pose identification. The work is among the first efforts to analyze gait motions into gait pose and gait posture, and it could be applied to a broad class of human activities in a number of situations.

• Advances in robotics research
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• v.1 no.1
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• pp.81-99
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• 2014

This paper contributes towards the development of a computer vision system for telemonitoring of industrial articulated robotic arms. The system aims to provide precision real time measurements of the joint angles by employing low cost cameras and visual markers on the body of the robot. To achieve this, a mathematical model that connects image features and joint angles was developed covering rotation of a single joint whose axis is parallel to the visual projection plane. The feature that is examined during image processing is the varying area of given circular target placed on the body of the robot, as registered by the camera during rotation of the arm. In order to distinguish between rotation directions four targets were used placed every $90^{\circ}$ and observed by two cameras at suitable angular distances. The results were deemed acceptable considering camera cost and lighting conditions of the workspace. A computational error analysis explored how deviations from the ideal camera positions affect the measurements and led to appropriate correction. The method is deemed to be extensible to multiple joint motion of a known kinematic chain.