• Korean Journal of Applied Biomechanics
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• v.13 no.1
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• pp.1-12
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• 2003

The purpose of this study was to design the method of 3D space calibration to reduce RMSE by statistical analysis when using the DLT algorithm and control frame. Control frame for 3D space calibration was consist of $1{\times}3{\times}2m$ and 162 contort points adhere to it. For calculate of 3D coordination used two methods about 2D coordination on image frame, 2D coordinate on each image frame and mean coordination. The methods of statistical analysis used one-way ANOVA and T-test. Significant level was ${\alpha}=.05$. The compose of methods for reduce RMSE were as follow. 1. Use the control frame composed of 24-44 control points arranged equally. 2. When photographing, locate control frame to center of image plane(image frame) o. use the lens of a few distortion. 3. When calculate of 3D coordination, use mean of 2D coordinate obtainable from all image frames.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1209-1221
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• 2010

Three dimensional (3D) video is expected to be an important application for broadcast and IP streaming services. One of the main limitations for the transmission of 3D video over IP networks is network bandwidth mismatch due to the large size of 3D data, which causes fatal decoding errors and mosaic-like damage. This paper presents a novel selective frame discard method to address the problem. The main idea of the proposed method is the symmetrical discard of the two dimensional (2D) video frame and the depth map frame. Also, the frames to be discarded are selected after additional consideration of the playback deadline, the network bandwidth, and the inter-frame dependency relationship within a group of pictures (GOP). It enables the efficient utilization of the network bandwidth and high quality 3D IPTV service. The simulation results demonstrate that the proposed method enhances the media quality of 3D video streaming even in the case of bad network conditions.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.635-641
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• 2009

본 논문에서는 다양한 휴대형 단말기기의 플랫폼 친화적이며 컨텐츠 개발의 신속성, 확장성 및 용이성이 고려된 3D 컨텐츠 플랫폼 엔진과 Application Frame 기술을 Convergence하였으며, Mobile Device에 탑재 가능한 3D 그래픽 사용자 인터페이스(GUI)의 시제품을 제작 및 응용하고, Mobile Game 등 컨텐츠의 개발을 효과적으로 빠르고 쉽게 구현할 수 있는데 필요한 3D GUI 객체(widget) 및 툴킷을 포함하는 Frame을 표준화 하는데 기본이 되는 연구를 하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.143-148
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• 1995

In this paper, we describe a fast 3D video segmentation method using mathematical morphology. The proposed 3D video segmentation algorithm is composed of intra-frame segmentation step and inter-frame segmentation step. In the intra-frame segmentation step, the first frame is segmented using the fast hierarchical segmentation method. Then, in the inter-frame segmentation step, the next frames are segmented using markers that are extracted from the difference of previous segmentation result and simplified present image. Experimental results show that the proposed method has more fast structure and is suitable for video segmentation.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.1-9
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• 2016

In order to reconstruct a 3D model in video sequences, to select key frames that are easy to estimate a geometric model is essential. This paper proposes a method to easily extract informative frames from a handheld video. The method combines selection criteria based on appropriate-baseline determination between frames, frame jumping for fast searching in the video, geometric robust information criterion (GRIC) scores for the frame-to-frame homography and fundamental matrix, and blurry-frame removal. Through experiments with videos taken in indoor space, the proposed method shows creating a more robust 3D point cloud than existing methods, even in the presence of motion blur and degenerate motions.

• Smart Media Journal
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• v.9 no.1
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• pp.23-29
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• 2020

This paper presents an approach for dynamic hand gesture recognition by using algorithm based on 3D Convolutional Neural Network (3D_CNN), which is later extended to 3D Residual Networks (3D_ResNet), and the neural network based key frame selection. Typically, 3D deep neural network is used to classify gestures from the input of image frames, randomly sampled from a video data. In this work, to improve the classification performance, we employ key frames which represent the overall video, as the input of the classification network. The key frames are extracted by SegNet instead of conventional clustering algorithms for video summarization (VSUMM) which require heavy computation. By using a deep neural network, key frame selection can be performed in a real-time system. Experiments are conducted using 3D convolutional kernels such as 3D_CNN, Inflated 3D_CNN (I3D) and 3D_ResNet for gesture classification. Our algorithm achieved up to 97.8% of classification accuracy on the Cambridge gesture dataset. The experimental results show that the proposed approach is efficient and outperforms existing methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.439-440
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• 2006

This research proposes a novel method of shape display to present 3-dimensional objects. Shape displays allow us to feel the actual volume of the object, unlike conventional 2D visual displays of 3D objects. The proposed method employs a wire frame structure to present 3D objects. The wire frame is composed of small units driven by shape memory alloy(SMA) actuators. The drive unit is analogous to the agonist-antagonist system of animal musculoskeletal systems, where the SMA actuators serve as agonist and antagonist muscles. The force in the SMA actuator is controlled by electrical current. The drive unit is equipped with the locking mechanism so that it can sustain the external force exerted by the user as well as the own weight of the wire frame structure. By controlling the current into the SMA actuator and locking mechanism, we call control the angle of the drive unit. A chain of drive units enables presentation of 2 dimensional objects. 3 dimensional presentations are possible by collecting the chains of drive units.

• Journal of KIBIM
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• v.8 no.2
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• pp.41-50
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• 2018

The current study focused on the utilization of building information modeling (BIM) data in steel-frame structures, which help to reduce project durations because they employ prefabricated structural members that are assembled on-site. In addition, a business process model was proposed using BIM data collected during the preconstruction, structural steel fabrication, and on-site construction phases of an actual steel-frame project. The ultimate expectation is that BIM data support at each phase, as well as the increased understanding among project participants, will result in an increase in project management productivity. The results from the current study are summarized as follows: To implement a BIM capable of application to steel-frame projects and data utilization, existing theories were studied to develop the construction project steps, both generally into the preconstruction (A1), steel fabrication (A2), and on-site construction phases, (A3) and specifically into 19 BIM-applicable phases. Based on the derived BIM-applicable phases, the model elements of the BIM object were identified, and the shortcomings of existing steel-frame projects were ameliorated, resulting in an improved data flow model. Moreover, for the proposed BIM data flow to progress efficiently, the BIM specialist needs to be well-acquainted with the phase-specific three-dimensional (3D) model output, and the infrastructure to construct an error-free 3D model must be provided. Based on the actual construction example, the BIM data utilized steel-frame projects - via production reports, clash checks, two-dimensional (2D) drawings, four-dimensional (4D) simulations, and 3D scanning - to make cooperation and communication among participants easier.

• Advances in aircraft and spacecraft science
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• v.2 no.3
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• pp.233-248
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• 2015

Frame structures have been traditionally represented as an assembling of components, these last described within the beam theory framework. In the case of frames involving complex components in which classical beam theory could fail, 3D descriptions seem the only valid route for performing accurate enough analyses. In this work we propose a framework for frame structure analyses that proceeds by assembling the condensed parametric rigidity matrices associated with the elementary beams composing the beams involved in the frame structure. This approach allows a macroscopic analysis in which only the condensed degrees of freedom at the elementary beams interfaces are considered, while fine 3D parametric descriptions are retained for local analyses.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.243-248
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• 2014

This study presents an investigation into the ways to detect the areas of object movement with Kinect's Depth Frame, which is capable of receiving 3D information regardless of external light sources. Applied to remove noises along the boundaries of objects among the depth information received from sensors were the blurring technique for the x and y coordinates of pixels and the frequency filter for the z coordinate. In addition, a clustering filter was applied according to the changing amounts of adjacent pixels to extract the areas of moving objects. It was also designed to detect fast movements above the standard according to filter settings, being applicable to mobile robots. Detected movements can be applied to security systems when being delivered to distant places via a network and can also be expanded to large-scale data through concerned information.