• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.641-644
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• 2015

In this paper, we propose a precise frame-level near-duplicate video matching algorithm. First, a binary frame descriptor for near-duplicate video matching is proposed. The binary frame descriptor divides a frame into patches and represent the relations between patches in bits. Seconds, we formulate a cost function for the matching, composed of matching costs and compensatory costs. Then, we roughly determine initial matchings and refine the matchings iteratively to minimize the cost function. Experimental results demonstrate that the proposed algorithm provides efficient performance for frame-level near duplicate video matching.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.155-160
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• 2016

Applying image processing techniques to education, the face of the learner is photographed, and expression and movement are detected from video, and the system which estimates degree of concentration of the learner is developed. For one learner, the measuring system is designed in terms of estimating a degree of concentration from direction of line of learner's sight and condition of the eye. In case of multiple learners, it must need to measure each concentration level of all learners in the classroom. But it is inefficient because one camera per each learner is required. In this paper, position in the face region is estimated from video which photographs the learner in the class by the difference between frames within the motion direction. And the system which detects the face direction by the face part detection by template matching is proposed. From the result of the difference between frames in the first image of the video, frontal face detection by Viola-Jones method is performed. Also the direction of the motion which arose in the face region is estimated with the migration length and the face region is tracked. Then the face parts are detected to tracking. Finally, the direction of the face is estimated from the result of face tracking and face parts detection.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.67-90
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• 2019

Accurate detection, tracking and analysis of human movement using robots and other visual surveillance systems is still a challenge. Efforts are on to make the system robust against constraints such as variation in shape, size, pose and occlusion. Traditional methods of detection used the sliding window approach which involved scanning of various sizes of windows across an image. This paper concentrates on employing a state-of-the-art, hierarchical graph based method for segmentation. It has two stages: part level segmentation for color-consistent segments and object level segmentation for category-consistent regions. The tracking phase is achieved by employing SIFT keypoint descriptor based technique in a combined matching and tracking scheme with validation phase. Localization of human region in each frame is performed by keypoints by casting votes for the center of the human detected region. As it is difficult to avoid incorrect keypoints, a consensus-based framework is used to detect voting behavior. The designed methodology is tested on the video sequences having 3 to 4 persons.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.155-162
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• 2014

In this paper, we propose an efficient shaking correction techniques for a moving vehicle image stabilization. The proposed shaking correction techniques was calculated cumulative histogram for the conversion and the separating information via color separation of video image frame of the input received. And it were to matching the histogram for match the color information as compensation result of the shaking vehicle video imaging. In this paper, the proposed the shaking correction techniques was obtained to the restoration result when compared to the existing shaking correction techniques that the smallest noise and better the naturalness of image through stabilization of luminance level and color level. Also, the imaging stabilization method was demonstrated the efficiency compared to other methods through to the real-time processing without the use of the memory.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.259-266
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• 2003

In this paper, we propose a multi-level block matching algorithm using motion information in blocks. In the proposed algorithm, the block-level is decided by the motion degree in the block before motion searching procedure, and then adequate motion searching performs according to the block-level. This improves computational efficiency by eliminating the unnecessary searching Process in no motion or low motion regions, and brings more accurate estimation results by deepening motion searching Process in high motion regions. Simulation results show that the proposed algorithm brings the lower estimation error about 20％ MSE reduction with the fewer blocks pet frame and the operation number was reduced to 56% compared to TSSA and 98% compared to FS -BMA with constant block size.

• Journal of Broadcast Engineering
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• v.12 no.2
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• pp.128-136
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• 2007

Since the multi-view video is a set of video sequences captured by multiple array cameras for the same three-dimensional scene, it can provide multiple viewpoint images using geometrical manipulation and intermediate view generation. Although multi-view video allows us to experience more realistic feeling with a wide range of images, the amount of data to be processed increases in proportion to the number of cameras. Therefore, we need to develop efficient coding methods. One of the possible approaches to multi-view video coding is to generate an intermediate image using view interpolation method and to use the interpolated image as an additional reference frame. The previous view interpolation method for multi-view video coding employs fixed size block matching over the pre-determined disparity search range. However, if the disparity search range is not proper, disparity error may occur. In this paper, we propose an efficient view interpolation method using initial disparity estimation, variable block-based estimation, and pixel-level estimation using adjusted search ranges. In addition, we propose a multi-view video coding method based on H.264/AVC to exploit the intermediate image. Intermediate images have been improved about $1{\sim}4dB$ using the proposed method compared to the previous view interpolation method, and the coding efficiency have been improved about 0.5 dB compared to the reference model.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.7
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• pp.53-60
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• 2009

Motion estimation for H.264/AVC video CODEC is very complex and requires a huge amount of computational efforts because it uses multiple reference frames and variable block sizes. We propose the architecture of high-performance integer-pixel motion estimation circuit based on fast algorithms for multiple reference frame selection, block matching, block mode decision and motion vector estimation. We also propose the architecture of high-performance interpolation circuit for sub-pixel motion estimation. We described the RTL circuit in Verilog HDL and synthesized the gate-level circuit using 130nm standard cell library. The integer-pixel motion estimation circuit consists of 77,600 logic gates and four $32\times8\times32$-bit dual-port SRAM's. It has tile maximum operating frequency of 161MHz and can process up to 51 D1 (720$\times$480) color in go frames per second. The fractional motion estimation circuit consists of 22,478 logic gates. It has the maximum operating frequency of 200MHz and can process up to 69 1080HD (1,920$\times$1,088) color image frames per second.