• Title/Summary/Keyword: Pose Analysis

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Error Quantification of Photogrammetric 6DOF Pose Estimation (사진계측기반 6자유도 포즈 예측의 오차 정량화)

  • Kim, Sang-Jin;You, Heung-Cheol;Reu, Taekyu
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.5
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    • pp.350-356
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    • 2013
  • Photogrammetry has been widely used for measuring the important physical quantities in aerospace areas because it is a remote and non-contact measurement method. In this study, we analyzed photogrammetric error which can be occur in six degrees of freedom(6DOF) analysis among coordinates systems with single camera. Error analysis program were developed, and validated using geometric problem converted from imaging process. We analogized that the statistic from estimated camera pose which is need to 6DOF analysis is normally distributed, and quantified the photogrammetric error using estimated population standard deviation.

Changes in Body Surface Lines Caused By Lower Limb Movements in Designing Slacks (I) (슬랙스 설계를 위한 하지동작에 따른 체표선 변화 1)

  • Cho Sung-Hee
    • Korean Journal of Human Ecology
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    • v.7 no.3
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    • pp.15-33
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    • 2004
  • A precise understanding of the human form in static pose serves as the basis of designing clothing. When the human body is in motion, however, even an article of clothing designed to fit the human form in static pose can pull and change, thus restricting the body. In order to increase the fit of the clothing, which may be termed the second skin, its form and measurements therefore must be determined in correlation not only with the formal characteristics of the human body, in static pose but also with its functional characteristics in motion, as caused by the movements of the human body. In this study, the motion factor was selected as the primary basis for designing slacks with good fit in both static and moving states. By indentifying the areas in which lower limb movement cause significant changes in body surface lines, we suggest several application methods for designing slacks. Using unmarried female university students aged 18 - 24 as subjects, a total of 32 body surface categories (15 body surface lines and 17 body surface segment lines) were measured in one static and 9 movement poses. In particular, expansion and contraction levels and rates were measured and used in the analysis. The analysis first involved the calculation of the average measurement per body part in body surface line in static pose as well as of the average expansion and contraction levels and rates in 9 lower limb movements. Two-way MANOVA and multiple comparison analysis (Tukey) were conducted on movements and individual somatotypes regarding measurement per body part and expansion and contraction rates. Body parts whose measurements of body surface lines differed significantly in body surface line in static pose versus in movement were then identified. The results of this study are as follows. First, changes in body surface lines caused by lower limb movements were significant in all body surface lines of the lower trunk, both horizontal and vertical, with the exception of abdomen girth, midway thigh girth, ankle girth, hip length, and posterior knee girth. Second, significantly expanded 10 body surface lines in moving pose were detected and illustrated in table 4. These body parts should be studied in designing or pattern designing, especially for close-fitting pants, in using stretch fabric, and in sensory evaluation of good fit during movement.

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A Parallel Implementation of Multiple Non-overlapping Cameras for Robot Pose Estimation

  • Ragab, Mohammad Ehab;Elkabbany, Ghada Farouk
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.11
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    • pp.4103-4117
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    • 2014
  • Image processing and computer vision algorithms are gaining larger concern in a variety of application areas such as robotics and man-machine interaction. Vision allows the development of flexible, intelligent, and less intrusive approaches than most of the other sensor systems. In this work, we determine the location and orientation of a mobile robot which is crucial for performing its tasks. In order to be able to operate in real time there is a need to speed up different vision routines. Therefore, we present and evaluate a method for introducing parallelism into the multiple non-overlapping camera pose estimation algorithm proposed in [1]. In this algorithm the problem has been solved in real time using multiple non-overlapping cameras and the Extended Kalman Filter (EKF). Four cameras arranged in two back-to-back pairs are put on the platform of a moving robot. An important benefit of using multiple cameras for robot pose estimation is the capability of resolving vision uncertainties such as the bas-relief ambiguity. The proposed method is based on algorithmic skeletons for low, medium and high levels of parallelization. The analysis shows that the use of a multiprocessor system enhances the system performance by about 87%. In addition, the proposed design is scalable, which is necaccery in this application where the number of features changes repeatedly.

Robust Head Pose Estimation for Masked Face Image via Data Augmentation (데이터 증강을 통한 마스크 착용 얼굴 이미지에 강인한 얼굴 자세추정)

  • Kyeongtak, Han;Sungeun, Hong
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.944-947
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    • 2022
  • Due to the coronavirus pandemic, the wearing of a mask has been increasing worldwide; thus, the importance of image analysis on masked face images has become essential. Although head pose estimation can be applied to various face-related applications including driver attention, face frontalization, and gaze detection, few studies have been conducted to address the performance degradation caused by masked faces. This study proposes a new data augmentation that synthesizes the masked face, depending on the face image size and poses, which shows robust performance on BIWI benchmark dataset regardless of mask-wearing. Since the proposed scheme is not limited to the specific model, it can be utilized in various head pose estimation models.

An Efficient Camera Calibration Method for Head Pose Tracking (머리의 자세를 추적하기 위한 효율적인 카메라 보정 방법에 관한 연구)

  • Park, Gyeong-Su;Im, Chang-Ju;Lee, Gyeong-Tae
    • Journal of the Ergonomics Society of Korea
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    • v.19 no.1
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    • pp.77-90
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    • 2000
  • The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

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CUDA-based Fast DRR Generation for Analysis of Medical Images (의료영상 분석을 위한 CUDA 기반의 고속 DRR 생성 기법)

  • Yang, Sang-Wook;Choi, Young;Koo, Seung-Bum
    • Korean Journal of Computational Design and Engineering
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    • v.16 no.4
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    • pp.285-291
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    • 2011
  • A pose estimation process from medical images is calculating locations and orientations of objects obtained from Computed Tomography (CT) volume data utilizing X-ray images from two directions. In this process, digitally reconstructed radiograph (DRR) images of spatially transformed objects are generated and compared to X-ray images repeatedly until reasonable transformation matrices of the objects are found. The DRR generation and image comparison take majority of the total time for this pose estimation. In this paper, a fast DRR generation technique based on GPU parallel computing is introduced. A volume ray-casting algorithm is explained with brief vector operations and a parallelization technique of the algorithm using Compute Unified Device Architecture (CUDA) is discussed. This paper also presents the implementation results and time measurements comparing to those from pure-CPU implementation and open source toolkit.

Full Pose Measurement of a Robot by the Wire Parallel Mechanism (와이어 병렬 메카니즘에 의한 로봇의 완전 자세 측정)

  • Jeong, Jae Won;Kim, Soo Hyun;Kwak, Yoon Keun
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.5
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    • pp.134-142
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    • 1997
  • In this study, we proposed the wire parallel mechanism that can be used to measure a full pose of a robot. It is composed of six parallel links using wire. The position and orientation of the end effectorf of a robot are calculated using the length of wires which is measured by the encoder. The complex non- linear equations of the forward kinematics are solved by using a numerical method, and the unique solution is obtained from the geometric configuration of the device. The length error of the wire which occurs in static condition is compensated by the relational equation that considered longitudinal extension and defoection of the wire. Through this work, we known that the proposed device has a good accuracy( .+-. 0.01mm) in a large measuring region, so it can be used effectively in a callibration of a robot which required a low cost.

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Pose Estimation Techniques for Humanoid Characters in FPS Gaming Environments (인간 캐릭터 포즈 식별: FPS 게임에서의 포즈 추정 기법)

  • Youjung Han;Minseop Lee;Minsu Cha;Jiyoung Woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.29-30
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    • 2024
  • 본 논문은 Krafton의 PUBG: BATTLEGROUNDS 게임에서 플레이어 분류를 목표로 하며, 포즈 추정기술을 사용하여 일반 플레이어와 봇을 구분한다. 이는 게임에서 직접 수집한 비디오 데이터를 기반으로 하며, 다음과 같은 두 가지 접근 방식을 제안한다. 첫 번째 방법은 동작 시퀀스 분석을 통해, 사용자의 특정동작 패턴을 식별하고 로지스틱 회귀 모델을 활용해 사용자 유형을 분류한다. 두 번째 방법은 YOLO-pose 모델을 사용하여 비디오 데이터에서 키포인트를 추출하고, 이를 LSTM 모델에 적용하여 프레임별로 사용자의 유형을 분류한다. 이러한 이중 접근 방식은 게임의 공정성과 사용자 경험을 향상시키는 새로운 도구를 제공하며, 보다 안전한 게임 환경에 기여할 수 있다. 이 연구는 게임 산업뿐만 아니라 보안 및 모니터링 분야에서도 동작 분석에 대한 혁신적인 접근 방식으로 활용될 잠재력을 가지고 있다.

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A Study on Hand Recognition in Image for Multimedia System (멀티미디어 시스템을 위한 영상내의 손 인식에 관한 연구)

  • Jung Hye-Won;Yang Hwan-Seok
    • The Journal of the Korea Contents Association
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    • v.5 no.2
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    • pp.267-274
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    • 2005
  • In this paper, we proposed an algorithm which cognize hand pose in real time using only image. Hand recognizes using edge orientation histogram which comes under a constant quantity of 2D appearance because hand pose is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantify, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Besides, principal component space creation time is reduced remarkably because edge directional data is used.

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