• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.322-325
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• 2005

TTX(Tilting Train eXpress) is being designed for improving the speed of conventional railway. The purpose of this study is to evaluate energy absorbing capacity and driver's survivability for a design candidate of the front end structure of TTX. A FE model with honeycomb block, under frame, and body frame is generated for crash simulation. Based on a level-crossing accident scenario, numerical simulation is performed using LS-DYNA. The results of crash analysis show that strength improvement of the current front end structure design candidate is needed to ensure driver safety.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2040-2043
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• 2003

General-purpose MPEG-2 video transcoders must be able to achieve any conversion between 18 ATSC (Advanced television system committee) video formats for DTV (digital television), e.g., scan format, size format, and frame rate format conversion. Especially, scan format conversion is hard to implement because frame rate and size format conversion often happen together. This paper proposes a fast motion estimation(ME) algorithm for MPEG-2 video transcoding supporting scan format conversion. Firstly, we extract and compose a set of candidate motion vectors (MV's) from the input bit-stream to comply with the re-encoding format. Secondly, the best MV is chosen among several candidate MV's by using a weighted median selector. Simulation results show that the proposed ME algorithm reduces significantly transcoding complexity with a minor PSNR degradation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.419-420
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• 2006

In the new video coding standard H.264/AVC, motion estimation (ME) is allowed to search multiple reference frames for improve the rate-distortion performance. The complexity of multi-frame motion estimation increases linearly with the number of used reference frame. However, the distortion gain given by each reference frame varies with the video sequence, and it is not efficient to search through all the candidate frames. In this paper, we propose a fast mult-frame selection method using all zero coefficient block (AZCB) prediction and sum of difference (SAD) of neighbor block. Simulation results show that the speed of the proposed algorithm is up to two times faster than exhaustive search of multiple reference frames with similar quality and bit-rate.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.179-182
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• 2001

In this paper. a key frame extraction algorithm for browsing and searching the summary of a video is proposed. Toward this end, important frames representing a shot are selected according to the correlations among frames. by using the Fourier descriptor which is useful for the shot boundary detection. To quantitatively evaluate the importance of selected frames. a new measure based on correlation coefficients of frames is proposed. If there are several frames with a same importance. another criteria is introduced to break the tie. by computing the partial moment of subframes including each candidate key frame so that the distortion rate is minimized Since a key frame extraction algorithm can be evaluated subjectively. the performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 20% improvement has been obtained by the proposed algorithm compared to existing methods.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.138-148
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• 2015

Object detection methods based on background learning are widely used in video surveillance. However, when a car runs with headlights on, these methods are likely to detect the car region and the area illuminated by the headlights as one connected change region. This paper describes a method of separating the car region from the area illuminated by the headlights. First, we detect change regions with a background learning method, and extract blobs, connected components in the detected change region. If a blob is larger than the maximum object size, we extract candidate object regions from the blob by clustering the intensity histogram of the frame difference between the mean of background images and an input image. Finally, we compute the similarity between the mean of background images and the input image within each candidate region and select a candidate region with weak similarity as an object region.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1040-1057
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• 2014

In this paper, a new bit rate estimation scheme is proposed to determine the bit rate for each subclass in an MPEG-2 TS to H.264/AVC transcoder after dividing an input MPEG-2 TS sequence into several subclasses. Video format transcoding in conventional IPTV and Smart TV services is a time-consuming process since the input sequence should be fully transcoded several times with different bit-rates to decide the bit-rate suitable for a service. The proposed scheme can automatically decide the bit-rate for the transcoded video sequence in those services which can be stored on a video streaming server as small as possible without losing any subject quality loss. In the proposed scheme, an input sequence to the transcoder is sub-classified by hierarchical clustering using a parameter value extracted from each frame. The candidate frames of each subclass are used to estimate the bit rate using a statistical analysis and a mathematical model. Experimental results show that the proposed scheme reduces the bit rate by, on an average approximately 52% in low-complexity video and 6% in high-complexity video with negligible degradation in subjective quality.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.688-693
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• 2007

Most frame structures cannot be manufactured in a single-piece form. Ideally, when a structure is built up by assembling multi pieces, assembly at the joints should be rigidly performed enough to have almost full stiffness, which is difficult for practical reasons such as manufacturing cost and time. In this research, we aim to develop a manufacturability-oriented compliance-minimizing topology optimization using a ground beam model incorporating additional zero-length elastic joint elements. In the present formulation, design variables control the stiffness of zero-length elastic joints, not the stiffness of beams. Because joint stiffness values at the converged state can be utilized to select candidate assembly locations and their strengths, the technique is extremely useful to design multi-piece frame structures. An optimal layout is also extracted based on the stiffness values.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.420-423
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• 1999

In this paper, we propose the method which efficiently obtain information through edit and retrieval of video data easily and rapidly. To support this method, extract the candidate representative frame using existing scene change detection method and the user selects representative frame for video segmentation at his desire, and then visualization indexing methods supported by logical-links enable users to freely merge and split each scene.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.467-473
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• 2004

Caption in video plays an important role that delivers video content. Existing caption region extraction methods are difficult to extract caption region from background because they are sensitive to noise. This paper proposes the method to extract caption region in sports video using multiple frame merge and MBR(Minimum Bounding Rectangles). As preprocessing, adaptive threshold can be extracted using contrast stretching and Othu Method. Caption frame interval is extracted by multiple frame merge and caption region is efficiently extracted by median filtering, morphological dilation, region labeling, candidate character region filtering, and MBR extraction.