• Journal of the Korea Computer Industry Society
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• v.9 no.4
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• pp.149-156
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• 2008

There is the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the proposed algorithm has better detection performance, such as recall rate, then the existing method. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.94-101
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• 2002

In this paper, we propose a motion estimation algorithm for the discontinuity blocks. The algorithm uses sub-SAD value (i.e. the sum of absolute difference for a quarter of a block) to identify the discontinuity region, and produces additional motion vectors for these sub-blocks if necessary. We show with experimental results that, in comparison with some conventional motion estimation algorithms, the proposed algorithm achieves quality enhancement for the sequences with discontinuity blocks, and also shows the same computational quantity as to normal algorithms for sequences with less discontinuity.

• Journal of the Semiconductor & Display Technology
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• v.13 no.1
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• pp.109-112
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• 2014

H.264/AVC is an international video coding standard that is established in cooperation with ITU-T VCEG and ISO/IEC MPEG, which shows improved code and efficiency than the previous video standards. Motion estimation using various macroblock from 44 to 1616 among the compression techniques of H.264/AVC contributes much to high compression efficiency. Generally, in the case of small motion vector or low complexity about P slice is decided $P16{\times}16$ mode encoding method. But according to circumstances, macroblock is decided $P16{\times}16$ mode despite large motion vector. If the motion vector variance is more than threshold and final select mode is $P16{\times}16$ mode, it is switched to $P8{\times}8$ mode, so this paper shows that the storage capacity is reduced. The results of experiment show that the proposed algorithm increases the compression efficiency of the H.264/AVC algorithm to 0.4%, even reducing the time and without increasing complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3315-3337
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• 2012

Crowded scenes analysis is a challenging topic in computer vision field. How to detect diverse motion patterns in crowded scenarios from videos is the critical yet hard part of this problem. In this paper, we propose a novel approach to mining motion patterns by utilizing motion information during both long-term period and short interval simultaneously. To capture long-term motions effectively, we introduce Motion History Image (MHI) representation to access to the global perspective about the crowd motion. The combination of MHI and optical flow, which is used to get instant motion information, gives rise to discriminative spatial-temporal motion features. Benefitting from the robustness and efficiency of the novel motion representation, the following motion pattern mining is implemented in a completely unsupervised way. The motion vectors are clustered hierarchically through automatic hierarchical clustering algorithm building on the basis of graphic model. This method overcomes the instability of optical flow in dealing with time continuity in crowded scenes. The results of clustering reveal the situations of motion pattern distribution in current crowded videos. To validate the performance of the proposed approach, we conduct experimental evaluations on some challenging videos including vehicles and pedestrians. The reliable detection results demonstrate the effectiveness of our approach.

• ETRI Journal
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• v.40 no.2
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• pp.266-274
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• 2018

In error-prone wireless environments, it is difficult to realize video coding systems that are robust to various types of data loss. In this paper, a novel motion-vector refinement approach is presented for video error concealment. A traditional boundary-matching approach is exploited to reduce blocky effects along the block boundary. More specifically, a downhill simplex approach is combined with a boundary-matching approach to fine-tune the motion vectors, reducing the blocky effects along the prediction unit block boundary, and minimizing the computational cost. Extensive simulations are performed, and the results obtained verify the robustness and effectiveness of the proposed approach.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.153-155
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• 2004

This paper proposes a real-time approach on the rotational motion estimation and correction for the roll stabilization of the sight system. This method first estimates a rotation center by the least-mean square algorithm based on the motion vectors of some feature points. And, then, a rotation angle is searched for a best matching block between a reference block image and seccessive input images using MPC(maximum pixel count) matching criterion. Finally, motion correction is performed by the bilinear interpolation technique. Various computer simulations show that the estimation performance is good and the proposed algorithm is a real-time implementable one to the TMS320C6415(500MHz) DSP.

• ETRI Journal
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• v.29 no.6
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• pp.826-828
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• 2007

Efficient downscaling in a transcoder is important when the output should be converted to a lower resolution video. In this letter, we suggest an efficient algorithm for transcoding from MPEG-4 SP (with simple profile) to H.264/AVC with spatial downscaling. First, target image blocks are classified into monotonous, complex, and very complex regions for fast mode decision. Second, adaptive search ranges are applied to these image classes for fast motion estimation in an H.264/AVC encoder with predicted motion vectors. Simulation results show that our transcoder considerably reduces transcoding time while video quality is kept almost optimal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.834-847
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• 1996

A selective coding scheme is proposed that describes a method for coding image sequences distinguishing bits between background and target region. The suggested method initially estimates global motion parameters and local motion vectors. Then segmentation is performed with a hierarchical clustering scheme and a quadtree algorithm in order to divide the processing image into the backgraound and target region. Finally image coding is done by assigning more bits to the target region and less bits to background so that the target region may be reconstructed with high quality. Simulations show that the suggested algorithm performs well especially in the circumstances where background changes and target regionis small enough compared with that of background.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.23-26
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• 2003

In this work. we propose an algorithm for detecting and compensating dynamic false contours in plasma display panels (PDPs). First, we detect the candidate pixels, which are likely to be corrupted by false contours, and merge those pixels into several regions. Second, we estimate the motion vectors of the selected regions. Finally, based on the motion information. we modify the luminance values of the pixels in the regions to alleviate the effects of false contours. Simulation results demonstrate that the proposed algorithm efficiently reduces dynamic false contours at low computational complexity.

• ETRI Journal
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• v.38 no.3
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• pp.502-509
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• 2016

Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, and $135^{\circ}$) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation.