• International Journal of Contents
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• v.12 no.1
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• pp.1-5
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• 2016

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.219-228
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• 2002

In this paper, we propose a new method of converting 2D video into 3D stereoscopic video, called stereoscopic conversion. In general, stereoscopic images are produced using the motion informations. However unreliable motion informations obtained especially from block-based motion estimation cause the wrong generation of stereoscopic images. To solve for this problem, we propose a stereoscopic conversion method based upon the utilization of key frame that has the better accuracy of estimated motion informations. As well, as generation scheme of stereoscopic images associated with the motion type of each key frame is proposed. For the performance evaluation of our proposed method, we apply it to five test images and measure the accuracy of key frame-based stereoscopic conversion. Experimental results show that our proposed method has the accuracy more than about 90 percent in terms of the detection ratio of key frames.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.113-120
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• 2004

In this paper, we propose an efficient feature extraction and image retrieval algorithm for content-based retrieval method. First, we extract the object using Gaussian edge detector for input image which is key frames of MPEG video and extract the object features that are location feature, distributed dimension feature and invariant moments feature. Next, we extract the characteristic color feature using the proposed HAQ(Histogram Analysis md Quantization) algorithm. Finally, we implement an retrieval of four features in sequence with the proposed matching method for query image which is a shot frame except the key frames of MPEG video. The purpose of this paper is to propose the novel content-based image retrieval algerian which retrieves the key frame in the shot boundary of MPEG video belonging to the scene requested by user. The experimental results show an efficient retrieval for 836 sample images in 10 music videos using the proposed algorithm.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.677-689
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• 2018

Residual deformation is a crucial index that should be paid special attention in the performance-based seismic analyses of reinforced concrete (RC) structures. Owing to their superior re-centering capacity under earthquake excitations, the post-tensioned self-centering (PTSC) RC frames have been proposed and developed for engineering application during the past few decades. This paper presents a comprehensive assessment on the seismic fragility of a PTSC frame by simultaneously considering maximum and residual deformations. Bivariate limit states are defined according to the pushover analyses for maximum deformations and empirical judgments for residual deformations. Incremental Dynamic Analyses (IDA) are conducted to derive the probability of exceeding predefined limit states at specific ground motion intensities. Seismic performance of the PTSC frame is compared with that of a conventional monolithic RC frame. The results show that, taking a synthetical consideration of maximum and residual deformations, the PTSC frame surpasses the monolithic frame in resisting most damage states, but is more vulnerable to ground motions with large intensities.

• Steel and Composite Structures
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• v.19 no.2
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• pp.405-416
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• 2015

We proposed the concept of nominal rigidity of a long-span V-shaped rigid frame composite arch bridge, analyzed the effects of structural parameters on nominal rigidity, and derived a theoretical nominal rigidity equation. In addition, we discussed the selection of the arch-to-beam rigidity ratio and its effect on the distribution of internal forces, and analyzed the influence of the ratio on the internal forces. We determined the delimitation value between rigid arch-flexible beam and flexible arch-rigid beam. We summarized the nominal rigidity and arch to beam rigidity ratios of existing bridges. The results show that (1) rigid arch-flexible beam and flexible arch-rigid beam can be defined by the arch-to-beam rigidity ratio; (2) nominal rigidities have no obvious differences among the continuous rigid frame composite arch bridge, V-shaped rigid frame bridge, and arch bridge, which shows that nominal rigidity can reflect the global stiffness of a structure.

• Structural Engineering and Mechanics
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• v.62 no.1
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• pp.11-20
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• 2017

The base force element method (BFEM) is a new finite element method. In this paper, a degenerated 4-mid-node plane element from concave polygonal element of BFEM was proposed. The performance of this quadrilateral element with 4 mid-edge nodes in the BFEM on complementary energy principle is studied. Four examples of linear elastic analysis for plane frame structure are presented. The influence of aspect ratio of the element is analyzed. The feasibility of the 4 mid-edge node element model of BFEM on complementary energy principles researched for plane frame problems. The results using the BFEM are compared with corresponding analytical solutions and those obtained from the standard displacement finite element method. It is revealed that the BFEM has better performance compared to the displacement model in the case of large aspect ratio.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.58-66
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• 2009

Recently the emerging demands of the light-video encoder promotes lots of research efforts on DVC (Distributed Video Coding). As an appropriate video compression method, DVC has been studied, and Wyner-Ziv (WZ) video compression is its one representative structure. The WZ encoder splits the image into two kinds of frames, one is key frame which is compressed by conventional intra coding, and the other is WZ frame which is encoded by WZ coding. The WZ decoder decodes the key frame first, and estimates the WZ frame using temporal correlation between key frames. Estimated WZ frame (Side Information) cannot be the same as the original WZ frame due to the absence of the WZ frame information at decoder. As a result, the difference between the estimated and original WZ frames are regarded as virtual channel noise. The WZ frame is reconstructed by removing noise in side information. Therefore precise noise estimation produces good performance gain in WZ video compression by improving error correcting capability by channel code. But noise cannot be estimated precisely at WZ decoder unless there is good WZ frame information, and generally it is estimated from the difference of corresponding key frames. Also the estimated noise is limited by comparing with frame level noise to reduce the uncertainty of the estimation method. However these methods cannot provide good noise estimation for every frame or each bit plane. In this paper, we propose a noise nodel selection method which chooses a better noise model for each bit plane after generating candidate noise models. Experimental result shows PSNR gain up to 0.8 dB.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.213-216
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• 2001

Key frame extraction is an important method of summarizing a long video. This paper propose a technique to automatically extract several key frames representative of its content from video. We use the color layout descriptor to select key frames from video. For selection of key frames, we calculate similarity of color layout features extracted from video, and extract key frames using similarity. An important aspect of our algorithm is that does not assume a fixed number of key frames per video; instead, it selects the number of appropriate key frames of summarizing a long video Experimental results show that our method using color layout descriptor can successfully select several key frames from a video, and we confirmed that the processing speed for extracting key frames from video is considerably fast.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.405-412
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• 2014

Due to the popularity of mobile phones, Peer-to-Peer (P2P) content sharing in mobile phones is highly desirable, especially in a mobile data connection. In addition, there has been an increasing demand for content sharing applications for P2P communication in Android-based smartphones as ubiquitous mobile devices. However, due to wireless network limits, unstable characteristic and restricted storage space, mobile users confront challenges in establishing connections and sharing video frames with other users. To solve this issue, we propose an architectural design and implementation of key frame sharing application that uses Chord, a distributed lookup protocol to establish a content sharing platform for mobile devices, combined with the Chord SDK based on Android. Our proposed system enables users easily to share key information on video data in real-time over a wireless network without manual processing of devices which join or leave the group and cost associated with the 3G/4G network.