• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.428-438
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• 2020

The jitter in the digital videos lowers the visibility and degrades the efficiency of image processing and image compressing. In this paper, we propose a video stabilizer architecture based on triplet CNN and a method of synthesizing training datasets based on video synthesis. Compared with a conventional deep-learning video stabilization method, the proposed video stabilizer can reduce wobbling distortion.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.106-111
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• 2009

Real-time video stabilization technology is used in correction for the camera vibrations of the hand-held camera by hand or fixed camera by external condition. This paper is about the counterplan to cope with the vibration of the movie generated by the large external cause relatively. we use the movie stabilization parameters with the phase correlation method based the DFT to get the displacements of the current frame to the reference frame. we use the kalman filter for the efficient and stable searching works on the phase correlation map and present the proper conditions for the real-time processing through the experiments. We propose the measure to evaluate the capability of the video stabilizer which is the standard deviation of the brightness of the center block. and compare the capability for the video sequences randomly shifted and the jittered video sequences obtained from camera.

• Journal of IKEEE
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• v.19 no.2
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• pp.244-253
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• 2015

Please This paper presents method of video stabilization based on detection and adaptive motion smoothing filtering of undesirable motion. The proposed algorithm consists of two stages: the detection of undesirable motion and smoothing filtering of detected undesired motion. To incorporate desired properties into the motion smoothing process, the local maximum and the local minimum are defined in a set composed of the parameters of accumulative global motion. Using the local information, the constraints on detecting undesirable motions are defined. Based on these constraints, the alpha parameter of the alpha-trimmed means filter is adjusted, so that the degree of motion smoothing in the reconstructed video sequence is controlled. The experimental results demonstrated the capability of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3086-3103
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• 2017

Video images captured by vehicle cameras often contain blurry or dithering frames due to inadvertent motion from bumps in the road or by insufficient illumination during the morning or evening, which greatly reduces the perception of objects expression and recognition from the records. Therefore, a real-time electronic stabilization method to correct fuzzy video from driving recorders has been proposed. In the first stage of feature detection, a coarse-to-fine inspection policy and a scale nonlinear diffusion filter are proposed to provide more accurate keypoints. Second, a new antiblurry binary descriptor and a feature point selection strategy for unintentional estimation are proposed, which brought more discriminative power. In addition, a new evaluation criterion for affine region detectors is presented based on the percentage interval of repeatability. The experiments show that the proposed method exhibits improvement in detecting blurry corner points. Moreover, it improves the performance of the algorithm and guarantees high processing speed at the same time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.204-206
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• 2017

최근에 개인용 카메라를 통해 개인의 추억을 파노라마 영상으로 기록하는 것에 관심이 급증하고 있다. 파노라마 영상에 관심이 급증함에 따라 파노라마 영상을 제작하는 방법에 대해 여러 분야에서 연구가 많이 진행되고 있다. 일반적으로 개인용 카메라를 손으로 잡고 촬영하는 경우가 대부분이다. 손으로 잡고 촬영한 영상은 손 떨림에 의해 흔들린 영상이 된다. 이는 파노라마 영상을 만들 때 어려운 요소를 야기한다. 그러므로 흔들린 영상을 정합하고 안정화하는 연구는 매우 중요하다. 따라서 본 연구의 목적은 최근에 연구된 비디오 정합(Video Stitching)과 비디오 안정화(Video Stabilization)의 정확도 및 경향을 파악을 통해 빛의 변화가 빈번하고 움직임이 많은 콘서트 영상 정합에 이용될 아이디어 추출에 있다.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.817-828
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• 2017

In this paper, we propose an efficient stabilization algorithm for 360 VR sequence, where the geometric information and the relationship between various projection formats have been utilized. The proposed scheme consists of '1st stitching', 'extraction of wide angle picture from VR data', 'stabilization', and '2nd stitching'. The simulation results show that the proposed method outperforms the conventional algorithms in the viewpoint of image quality for end-user.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.13-20
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• 2010

We proposed a new technique to perform fast video stabilization using integral image in this article. In the proposed technique, it evaluate local and global motion by the block matching using the generated integral image for each frame and compensate the motion like jitter. We made the various experimental jitter patterns to evaluate the effectiveness of the proposed technique and evaluated stabilization capability and execution time with the existing ones. Through the experiment, we found that the execution time of proposed technique was faster than that of existing techniques and the compensation of jitter was well done.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.317-322
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• 2009

If vibration occurs due to fast movement of the robot, the camera image is unstable. No longer the eyes of a robot can not perform the role. Research methods for the stabilization of shaky video is required. The most popular method is to use the motion vector. But, the drawback to this method will require a large amount of operation. And the limits of the embedded robot. Therefore, in real-time transmission of images to be difficult. This paper proposes a motion sensor using the image stabilization. Uses data that is output from the motion sensor. So, not related to the progress of the robot movement is a way to remove it from the video.

• 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 the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.77-82
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• 2012

This paper presents a hardware-implemented face regions stabilization algorithm that stabilizes facial regions using the locations and sizes of human faces found by a face detection system. Face detection algorithms extract facial features or patterns determining the presence of a face from a video source and detect faces via a classifier trained on example faces. But face detection results has big variations in the detected locations and sizes of faces by slight shaking. To address this problem, the high frequency reduce filter that reduces variations in the detected face regions by taking into account the face range information between the current and previous video frames are implemented in addition to center distance comparison and zooming operations.