Korean Church Planters’ Perception on Church Planting Education

This studyseeks to understand how Korean church planters perceive the church planting education that they received. This study employs the qualitative approach, which uses words and open-ended questions to explore and understand the meaning that individuals or groups ascribe to a social or human problem. To collect data, I interviewed nine church planters. I analyzed, interpreted, and wrote data as soon as possible. In addition, I collected other data. I also compared different data with each other to generate categories, and it was done consistently. The followings are the findings. While their passion for church planting was great and their assumptions and lack of infrastructure inhibited their preparation for church planting, they learned through their various experiences and social networks

Korean Church Planters’ Perception on Church Planting Education

This studyseeks to understand how Korean church planters perceive the church planting education that they received. This study employs the qualitative approach, which uses words and open-ended questions to explore and understand the meaning that individuals or groups ascribe to a social or human problem. To collect data, I interviewed nine church planters. I analyzed, interpreted, and wrote data as soon as possible. In addition, I collected other data. I also compared different data with each other to generate categories, and it was done consistently. The followings are the findings. While their passion for church planting was great and their assumptions and lack of infrastructure inhibited their preparation for church planting, they learned through their various experiences and social networks

LInKs "Lifting Independent Keypoints" -- Partial Pose Lifting for Occlusion Handling with Improved Accuracy in 2D-3D Human Pose Estimation

We present LInKs, a novel unsupervised learning method to recover 3D human poses from 2D kinematic skeletons obtained from a single image, even when occlusions are present. Our approach follows a unique two-step process, which involves first lifting the occluded 2D pose to the 3D domain, followed by filling in the occluded parts using the partially reconstructed 3D coordinates. This lift-then-fill approach leads to significantly more accurate results compared to models that complete the pose in 2D space alone. Additionally, we improve the stability and likelihood estimation of normalising flows through a custom sampling function replacing PCA dimensionality reduction previously used in prior work. Furthermore, we are the first to investigate if different parts of the 2D kinematic skeleton can be lifted independently which we find by itself reduces the error of current lifting approaches. We attribute this to the reduction of long-range keypoint correlations. In our detailed evaluation, we quantify the error under various realistic occlusion scenarios, showcasing the versatility and applicability of our model. Our results consistently demonstrate the superiority of handling all types of occlusions in 3D space when compared to others that complete the pose in 2D space. Our approach also exhibits consistent accuracy in scenarios without occlusion, as evidenced by a 7.9% reduction in reconstruction error compared to prior works on the Human3.6M dataset. Furthermore, our method excels in accurately retrieving complete 3D poses even in the presence of occlusions, making it highly applicable in situations where complete 2D pose information is unavailable

Temporally coherent 4D reconstruction of complex dynamic scenes

This paper presents an approach for reconstruction of 4D temporally coherent models of complex dynamic scenes. No prior knowledge is required of scene structure or camera calibration allowing reconstruction from multiple moving cameras. Sparse-to-dense temporal correspondence is integrated with joint multi-view segmentation and reconstruction to obtain a complete 4D representation of static and dynamic objects. Temporal coherence is exploited to overcome visual ambiguities resulting in improved reconstruction of complex scenes. Robust joint segmentation and reconstruction of dynamic objects is achieved by introducing a geodesic star convexity constraint. Comparative evaluation is performed on a variety of unstructured indoor and outdoor dynamic scenes with hand-held cameras and multiple people. This demonstrates reconstruction of complete temporally coherent 4D scene models with improved nonrigid object segmentation and shape reconstruction.Comment: To appear in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016 . Video available at: https://www.youtube.com/watch?v=bm_P13_-Ds

Improvement of Diagnosis-Supplement System for Basic Academic Skill based on Affordance Theory in the Context of HCI

The purpose of this study is to apprehend a problem of user affordance and to suggest an improvement plan to make the better usability of Diagnosis-Supplement System for basic academic skill. Starting in 2013, from 5 cities and provinces, this system was developed, and in 2015, it was completed construction in all (17) provinces. Now, this system serves diagnosis test and supplement study materials for underachievement students from 3rd grade to 8th grade. As of 2015, the role of this system is gradually increased that 16 million students, about 4% of pupils throughout the country are now using it. In turn, this study tries to analyze various ranging requirements of teachers and experts by doing focus group interview in terms of user affordance and try to suggest the way to improve this system for the sustainable use. Henceforth the results of this study, which includes specific problems of physical, cognitive, sensual affordance and a design prototype to improve these problems, can be an important base material for the process of improving Diagnosis Supplement System for Basic Academic Skill with the effective and intuitive syste

Unsupervised Reconstruction of 3D Human Pose Interactions From 2D Poses Alone

Current unsupervised 2D-3D human pose estimation (HPE) methods do not work in multi-person scenarios due to perspective ambiguity in monocular images. Therefore, we present one of the first studies investigating the feasibility of unsupervised multi-person 2D-3D HPE from just 2D poses alone, focusing on reconstructing human interactions. To address the issue of perspective ambiguity, we expand upon prior work by predicting the cameras' elevation angle relative to the subjects' pelvis. This allows us to rotate the predicted poses to be level with the ground plane, while obtaining an estimate for the vertical offset in 3D between individuals. Our method involves independently lifting each subject's 2D pose to 3D, before combining them in a shared 3D coordinate system. The poses are then rotated and offset by the predicted elevation angle before being scaled. This by itself enables us to retrieve an accurate 3D reconstruction of their poses. We present our results on the CHI3D dataset, introducing its use for unsupervised 2D-3D pose estimation with three new quantitative metrics, and establishing a benchmark for future research

General Dynamic Scene Reconstruction from Multiple View Video

This paper introduces a general approach to dynamic scene reconstruction from multiple moving cameras without prior knowledge or limiting constraints on the scene structure, appearance, or illumination. Existing techniques for dynamic scene reconstruction from multiple wide-baseline camera views primarily focus on accurate reconstruction in controlled environments, where the cameras are fixed and calibrated and background is known. These approaches are not robust for general dynamic scenes captured with sparse moving cameras. Previous approaches for outdoor dynamic scene reconstruction assume prior knowledge of the static background appearance and structure. The primary contributions of this paper are twofold: an automatic method for initial coarse dynamic scene segmentation and reconstruction without prior knowledge of background appearance or structure; and a general robust approach for joint segmentation refinement and dense reconstruction of dynamic scenes from multiple wide-baseline static or moving cameras. Evaluation is performed on a variety of indoor and outdoor scenes with cluttered backgrounds and multiple dynamic non-rigid objects such as people. Comparison with state-of-the-art approaches demonstrates improved accuracy in both multiple view segmentation and dense reconstruction. The proposed approach also eliminates the requirement for prior knowledge of scene structure and appearance

FTA in international finance : impacts of exchange rates on FTA utilization

This paper investigates how exchange rates affect the utilization of a free trade agreement (FTA) scheme in trading. Changes in exchange rates affect FTA utilization by two ways. The first way is by changing the excess profits gained by utilizing the FTA scheme, and the second way is by promoting the compliance of rules of origin. Our theoretical models predict that the depreciation of exporters\u27 currency against that of importers enhances the likelihood of FTA utilization through those two channels. Furthermore, our empirical analysis, which is based on rich tariff-line-level data on the utilization of FTA schemes in Korea\u27s imports from ASEAN countries, supports the theoretical prediction. We also show that the effects are smaller for more differentiated products